Search

Antonymy is the lexical relation of opposition. The nature of the oppositeness may differ – e.g., contradictory (‘true’–‘false’) or gradable (‘tall’–‘short’) – and there may be variation as to the relationship in their formal encoding, whether the antonyms are expressed as distinct lexical forms (e.g., true vs. false) or if one form is derived from the other (e.g., true vs. untrue). We investigate the relationship between the two members of 37 antonym pairs across 55 spoken languages in order to see whether there are patterns in how antonymy is expressed and which of the two antonym members is more likely to be derived from the other. We find great variation in the extent to which languages use derivation (labeled “neg-constructed forms”) as an antonym-formation strategy. However, when we do find a derived form, this tends to target the member of the pair that is either lower in valence (positive vs. negative) or magnitude (more vs. less), in line with our hypotheses. We also find that antonyms that belong to a core set of property concepts are more likely to encode antonyms as distinct lexical forms, whereas peripheral property concepts are relatively more likely to encode the antonyms with derived forms.

Bu araştırmanın amacı, ilköğretim sürecinde zorunlu dersler kapsamında öğrenciler tarafından kullanılan ders kitaplarındaki söz varlığı ile ilgili bir durum analizi ortaya koymaktır. Nitel araştırma yönteminde durum çalışması deseninde yürütülen araştırma, 2018-2019 eğitim öğretim yılı örnekleminde 48 ders kitabı üzerinden gerçekleştirilmiş; doküman incelemesi yoluyla toplanan veriler, içerik analizleri ile değerlendirilmiştir. Ders kitaplarından elde edilen 1.058.434 biçimbirimsel (ham) söz varlığı, anlambirimsel olarak incelenmiş ve araştırmanın amacına uygun olarak literatürde daha önceden belirlenen ölçütler doğrultusunda işlenmiştir. Araştırma sonucunda öğrencilerin zorunlu dersler kapsamında işlenen ders kitaplarında toplam olarak 33.021’İ birbirinden farklı olmak üzere 949.355 söz varlığı unsuruyla karşılaştığı tespit edilmiştir. Bu unsurlardan 864.345’i (20.798 çeşit) temel söz varlığı, 170’i (113 çeşit) atasözü, 16.252’si (2.247 çeşit) deyim, 2.793’ü (636 çeşit) ikileme, 968’i (197 çeşit) kalıp söz, 43.792’si (6.110 çeşit) özel isim, 20.623’ü (2.733 çeşit) sayısal ifade, 412’si (187 çeşit) yabancı dillere ait söz varlığı unsuru olarak belirlenmiştir. Ders kitaplarında yalnızca bir kez kullanılmış olan 11.891 söz varlığı unsuru, ders kitaplarında geçen söz varlığı toplamının yaklaşık olarak %1,25’ini; birden çok tekrar eden 21.129 söz varlığı unsuru (toplamda 937.464 sıklık) ise ders kitaplarında geçen söz varlığı toplamının %98,75’ini oluşturmuştur. Ders kitaplarında en sık geçen ilk 2.002 söz varlığı unsuru ise çalışma ekinde paylaşılmıştır.

The main subject of this paper is the lexical-semantic classification of water-related lexicon in the novel Most (Bridge) by Jasmina Musabegović. We will explain the stylistic expressiveness of selected water-related lexemes, as well as the way the author constructs her identity and the identities of her characters through the conceptualization of the experience of water. The water lexics are analysed as dominant in relation to other types of words and classified into eleven lexical-semantic fields. Total of 79 water nouns have been registered. As expected, the most common water-related lexemes are ‘voda’ and ‘most’. Three water nouns are described: voda, most and tihanj, and it is concluded that lexeme ‘water’ has an associative and symbolic role; lexeme ‘most’, as a strong position of the text, since it is also a title of the novel, represents change, a path and growing up. The nonce word tihanj has a specific cultural and linguistic meaning in the context of the novel.

Text mining has led to growth in sentiment analysis (SA) across various research disciplines. The pandemic has provided a unique and special context for analysing students’ written expression. We utilised comments from a survey conducted during the pandemic to create a corpus for SA. The corpus comprises 25,197 words extracted from over 600 comments in Spanish, collected during a survey that lasted around 20 days. We aim to detect sentiments and emotions from this corpus using SA. However, some essential and little-discussed issues in literature should be addressed, such as its relationship with post-cognitivist theory. This paper uses the post-cognitivist approach to analyse emotions and sentiments through SA with the Spanish lexicon in the economics of education. Literature in this area needs further development, especially in Spanish. The article shows that the emotions and sentiments of students in challenging situations can be identified through a corpus of student comments. However, specific elements should be considered while interpreting emotions and sentiments within the framework of post-cognitivism methodologies. Recognising that the human experience is a complex interaction, it is essential to consider the emotional nuances within the context in which they develop. Addressing this issue from the post-cognitivist approach is one of several ways to carry out this task. Using SA and emotions to analyse a text corpus is still helpful for researchers who follow the post-cognitivist approach. However, combining this technique with other qualitative and in-depth computational methods is essential to fully understanding the emotional experiences within their respective contexts.

The intersection of two lexical-semantic fields “mentality” and “physiology” in the poetic texts of Igor-Severyanin is studied. The relevance of the research is determined by the fact that within the framework of modern anthropocentric approach and increased attention to the mental sphere lexical semantics is investigated, lexical-semantic fields, their intersections, semantic shifts are considered, actual problems of linguistic poetics are touched upon. The aim of the work is to explore the intersection of lexical-semantic fields “mentality” and “physiology” in the language of Severyanin's poems. The material includes lexemes of the mental sphere from Igor-Severyanin's poetic texts. While determining the usual meaning of these lexemes, the authors used the materials of “Explanatory Dictionary of the Russian Language” by S.I. Ozhegov. The methods of description, comparison, contrast, lexical-semantic and contextual analysis, and continuous sampling were applied; the lexical-semantic field - a generally accepted form of representing lexical units by their meaning - was used to structure the vocabulary. The intersections of the lexical-semantic fields “mentality” and “physiology” in Igor-Severyanin's texts, revealed in the research, are primarily due to the inseparable connection between the inner world of man and his bodily organs of sense. The language fixes stable expressions indicating the possibility of comprehending the human consciousness through analyzing the signals of his body. Words used to denote phenomena and processes related to the body, health, gestures, etc., are reinterpreted in poetic language and receive new semantics, which allows to refer these new lexical-semantic units to the lexical-semantic field of mentality. In Igor-Severyanin's poems the inner world of the lyrical subject dominates, which is reflected in the author's word usage. Even words and expressions with the semantics of physiology shift in their meanings, acquiring the semantics of mentality, at the same time thoughts and feelings are endowed with the author's positive evaluation. The prospects of the research are connected primarily with further study of the mental sphere in the Russian linguistic lexical-semantic system, its dynamics, as well as with the analysis of semantic shifts in the poetic language vocabulary.

This study unveils insights into the spatial and social distribution of Portuguese lexical forms, or lexies, pertaining to urban life in the interior of São Paulo State. These lexies were collected through oral responses from eighty participants, elicited by nine questions addressing variants for terms such as ‘traffic lights’, ‘speed bump’, ‘sidewalk’, ‘curb’, ‘traffic circle’, ‘plot of land’, ‘city bus’, ‘intercity bus’, and ‘a small grocery store where one can also drink liquor at a counter’. The analysis examines whether these lexies establish themselves as predominant norms, indicated by both consistent spatial distribution and a relative frequency exceeding 50% across the localities surveyed. Out of the nine cases studied, eight meet this criterion, with the following overall relative frequencies: ‘semáforo’ 53%; ‘lombada’ 96%; ‘calçada’ 94%; ‘guia’ 84%; ‘rotatória’ 74%; ‘terreno (baldio)’ 79%; ‘ônibus’ (in the sense of ‘city bus’) 71%; ‘ônibus’ (in the sense of ‘intercity bus’) 51%. The ninth variant, ‘bar,’ nearly meets this standard as well, with a relative frequency of 41% just falling short of the minimum threshold.

This study aimed to describe the flora lexicon for the reproductive health of the Tetun from an ecolinguistic perspective. The method was descriptive qualitative with an ethnolinguistic approach. The data were lexicon flora for female reproduction obtained from community leaders and traditional healers. Data collection techniques were carried out using observation, interviews, note-taking, and a literature study. Data analysis was carried out by classifying the forms, the linguistic form, and ecological categories. The results showed that there were 53 flora lexicons for reproductive health in the form of root words and derived words. Based on linguistic category, the 53 flora lexicons are classified as having animate meaning. Based on the ecological category, the 53 flora lexicons are biotic plants. Utilization of flora ingredients for reproductive health includes rhizomes, tubers, roots, bark, leaves, leaf shoots, flowers, fruits, and seeds. The method of processing is by boiling, cooking, pounding, chewing, drinking, eating, smearing, sticking, spraying, and pouring on the affected part.

This paper reviews PoLyInfo, which is a polymer database of National Institute for Materials Science of Japan, containing more than half a million data points, from the perspective of a data editor. In particular, we describe how human-readable information provided by a graphical user interface (GUI) is curated, compiled, and displayed on the GUI, and how it can be used for data retrieval. We also describe the data curation policy of PoLyInfo, which can be observed through search functions and data tables, and show the unique taxonomy of various polymers. The status of polymers and their potential and limitations, as seen through a large dataset, are discussed. With this information, we introduce the capabilities of PoLyInfo and provide guidelines for its use as a general database for polymer chemistry, as well as notes on newer data applications such as machine learning.

The present research aims to record and analyze the antivaccinationist language used during the COVID-19 pandemic, highlighting in particular the lexical aspects that characterize its identity, and to verify the possibility of recognizing it as a genuine and distinct jargon.

Childfree is a condition in which a person or couple decides not to have children in marriage. Childfree became popular in Indonesia when YouTuber and influencer Gita Savitri uploaded an Instagram story about it. This brought many pros and cons among the people towards the freedom to have children. Many TV broadcasts and YouTube videos cover this phenomenon. Several YouTube channels that broadcast this phenomenon are Menjadi Manusia and Analisa Channel. We collect YouTube comment data using web scraping techniques. From September 2021 to September 2022, 674 sample data points were obtained from two YouTube videos. Data is labelled (positive, negative, and neutral) using the Indonesian language lexicon approach as well as the Support Vector Machine (SVM) and Random Forest algorithms to determine the best model for classifying YouTube comments. The purpose of this research is to understand the public's perception of childfree and to compare the accuracy and AUC values of the two methods. Based on the results of the analysis, 128 comments are classified as positive, the remaining 39 comments are classified as neutral, and 503 comments are classified as negative. This shows that that the commentators on YouTube do not support or give a negative stigma to people who adhere to childfree. The solution to the balanced data problem for each sentiment class uses the random oversampling (ROS) approach. The RBF kernel SVM classification algorithm is a suitable method for classifying commentary data with an accuracy of 98.01% and an AUC of 98.58%, while the Random Forest algorithm only obtains an accuracy of 94.37% and an AUC of 95.87%.

I discuss the criteria of defining linguistics against other science branches. Lin­guistics is not a proper part of semiotics, since the foundations of language do not necessarily rely on the theory of sign systems. Grammar always operates on sets, including the sets consisting of one element. Not all language objects can be treated as signs. The connectors, i. e. segmental means marking the levels of clause linkage are legal linguistic objects, but the analysis of in­dividual texts is a prerogative of philological and interdisciplinary research.

Abstract Background A large body of literature indicates that connected speech profiles in patients with Alzheimer’s disease (AD) can be utilized for diagnosis, disease monitoring, and for developing communication strategies for patients. Most connected speech research has been conducted in English, with little work in some European languages. Therefore, significant drawback remains with respect to the diversity of languages studied, and how the fragmentation of linguistic features differs across languages in AD. Accordingly, existing reviews on connected speech in AD have focused on findings from English-speaking patients; none have specifically focused on the linguistic diversity of AD populations. This scoping review is undertaken to provide the currently reported characteristics of connected speech in AD in languages other than English. It also seeks to identify the type of assessments, methods to elicit speech samples, type of analysis and linguistic frameworks used, and micro- and macro-linguistic features of speech reported in non-English speakers with AD. Method We will conduct a scoping review of published studies that have quantitively assessed connected speech in AD in languages other than English. The inclusion criteria for the studies would be subject/s with a clinical diagnosis of AD. The search will include the electronic databases PubMed, Ovid-Embase, PsycINFO, Linguistic and Language Behaviour Abstracts (LLBA), and Web of Science up until March 2023. Findings will be mapped and described according to the languages studied, the methodology employed (e.g., patient characteristics, tasks used, linguistic analysis framework utilized), and connected speech profiles derived (e.g., micro- and macro-linguistic reported). Discussion The scoping review will provide an overview of languages studied in connected speech research in AD with variation in linguistic features across languages, thus allowing comparison with the established key features that distinguish AD patients from healthy controls. The findings will inform future research in connected speech in different languages to facilitate robust connected speech research in linguistically and ethnically diverse populations.

The subject of the article is the role of Honorius Balzac in the drama by Jarosław Iwaszkiewicz The Wedding of Mr. Balzac. Dialogues of various characters of the drama were analysed referring to the French novelist and the statements of Honorius himself Balzac. These studies showed by what means and how the author of the drama creates a multifaceted and psychologically deep portrait of the great artist.

Silver needle is a common type of white tea in Indonesia. The silver needle is produced from unbloomed pekoe, is pointed, slightly hairy, and silver in color. Quantitative descriptive analysis is a sensory evaluation method that relies on trained panelists' abilities in the experiment. The purpose of this study is to create a sensory profile of white tea from Indonesia using the QDA method. Five tea samples registered to the Indonesian National Agency for Drug and Food Control (Brand Gamboeng, Ennie 1, and Cap Pucuk from the West Java, Teh Dandang from Central Java, and Brand Heizl from East Java) were evaluated by trained panelists with extensive experience who had passed selection and training processes. Water was used as the neutralizer and crackers as the carrier. Three grams of each sample were brewed at 98°C with 150 mL of water for 7 min. Each panelist described the attribute, determined the reference, and evaluated all samples on a 15-cm scale. The results of the focus group discussion has obtained 12 lexicon sensory attributes, namely: yellow-brown, burned aroma, floral aroma, dry aroma, woody aroma, green aroma, burned flavor, green flavor, fermented flavor, floral flavor, bitter taste, astringent aftertaste, and bitter aftertaste. The results also showed that the "Heizl" white tea had the following sensory characteristics: yellow-brown, burned aroma, burned flavor, fermented flavor, bitter taste, bitter aftertaste, and astringent aftertaste. Moreover, the "Dandang" white tea had the following attributes: dry aroma, floral aroma, woody aroma, green aroma, green flavor, and floral flavor.

This research aims to identify and explain the meaning of various terms contained in the lexicon of Haul Bungah tradition and the cultural values reflected in these terms. The data of this research are terms related to aul Bungah tradition. The research method used is qualitative, with data collection techniques through participant observation and in-depth interviews. Recording and note-taking were also done to support data collection. The results showed that 17 terms are often used in the Haul Bungah tradition, which can be categorized into two forms, namely monomorphemic and polymorphemic. Based on the two forms, this research found 4 terms in monomorphemic form and 13 terms in polymorphemic form. The cultural values reflected from the lexicon in the Haul Bungah tradition include human relationships with God, nature, society, others, and oneself.

Sentiment is employed in various fields, such as collecting web-based opinions for the formulation of governmental policies, measuring employee and customer satisfaction levels in business organizations, and measuring the sentiment of the public in political and security matters. The field has recently faced new challenges since algorithms must operate with highly unstructured sentiment data from social media. In this study, the authors present a new stacking ensemble method that combines the lexicon-based approach with machine learning algorithms to improve the sentiment analysis of tweets. Due to the complexity of the text with very ill-defined syntactic and grammatical patterns, using lexicon-based techniques to extract sentiment from the content is proposed. On the same note, the contextual and nuanced aspects of sentiment are inferred through machine learning algorithms. A sophisticated bat algorithm that uses an Elman network as a meta-classifier is then employed to classify the extracted features accurately. Substantial evidence from three datasets that are readily available for public analysis re-affirms the improvements this innovative approach brings to sentiment classification.

This study harnesses the linguistic diversity of Arabic dialects to create two expansive corpora from X (formerly Twitter). The Gulf Arabic Corpus (GAC-6) includes around 1.7 million tweets from six Gulf countries—Saudi Arabia, UAE, Qatar, Oman, Kuwait, and Bahrain—capturing a wide range of linguistic variations. The Saudi Dialect Corpus (SDC-5) comprises 790,000 tweets, offering in-depth insights into five major regional dialects of Saudi Arabia: Hijazi, Najdi, Southern, Northern, and Eastern, reflecting the complex linguistic landscape of the region. Both corpora are thoroughly annotated with dialect-specific seed words and geolocation data, achieving high levels of accuracy, as indicated by Cohen’s Kappa scores of 0.78 for GAC-6 and 0.90 for SDC-5. The annotation process leverages AI-driven techniques, including machine learning algorithms for automated dialect recognition and feature extraction, to enhance the granularity and precision of the data. These resources significantly contribute to the field of Arabic dialectology and facilitate the development of AI algorithms for linguistic data analysis, enhancing AI system design and efficiency. The data provided by this research are crucial for advancing AI methodologies, supporting diverse applications in the realm of next-generation AI technologies.

By questioning the notion of ethos in utterance from an attested production of Vietnamese speeches, we make the postulate of the instruction of a collective ethos at the level of kinship terms. Moreover, dynamic discursive traces reveal the implicit encoding of this collective ethos. We rely on a concept of Vietnamese collective ethos: họ.

The Bosnian language holds significant importance as a member of the West-South Slavic subgroup within the Slavic branch of the Indo-European linguistic family. With approximately 2.5 million speakers in Europe, including 1.87 million individuals in Bosnia and Herzegovina alone, the Bosnian language constitutes the mother tongue for a considerable portion of the population.In Natural Language Processing (NLP) tasks related to the Bosnian language, besides removing stop words, it is important to consider the influence of other linguistic elements. Bosnian text contains words derived from diminishers, relative intensifiers, minimizers, maximizers, boosters, and approximators. These words contribute to the overall meaning and sentiment analysis of the text. By including these elements in NLP models and algorithms, researchers can achieve more accurate and nuanced analysis of Bosnian language data, enhancing the effectiveness of NLP applications.The two lists of sentiment annotated words that present the core of the Bosnian sentiment-annotated lexicon, a list of the stopwords, and a list of Affirmative and non-Affrimative words (AnAwords) composed mostly of intensifiers and diminishers, were used to construct a dataset that presents the base for sentiment analysis in the Bosnian language.

This article is situated within the context of exploring transnationality, circulation, and mobility as methodological devices/operational concepts in analyzing artistic artifacts, artists, and knowledge in motion. It delves into the interaction between art history and the global configuration of the contemporary age, reflecting on the application of methodological proposals from the global turn in the social sciences to the analysis of artistic mobility during the early modern period. Within this broader exploration, the article delves into the multifaceted nature of the genesis of reflections that have led to the emergence of global art history as a constellated phenomenon. It argues that the questioning of paradigms and the introduction of new terminology into the discipline cannot be solely attributed to art history itself. Instead, it emphasizes the need to examine the close association between this approach and broader movements of thought and historiography. At its core, the article highlights the crucial need for reevaluating language, lexicon, and research practices within historiographical movements. It advocates for the deconstruction of existing narratives and the creation of counter-narratives through a reconsideration of the terminology employed. This process fosters imaginative exploration bringing artistic analysis closer to current debates and ongoing reformulations of research practices.

Today, social media sites like Twitter provide effective platforms to share opinions and thoughts in public with millions of other users. These opinions shared on such sites influence a large number of people who may easily retweet them and accelerate their spread. Unfortunately, some of these opinions were expressed by extremists who promoted hateful content. Since Arabic is one of the most spoken languages, it is crucial to automate the process of monitoring Arabic content published on social sites. Therefore, this study aims to propose a hybrid technique to detect extremism in Arabic social media texts and articles to monitor the situation of published extremist content. The proposed technique combines the lexicon-based approach with the rough set theory approach. The rough set theory is employed with two approximation strategies: lower approximation and accuracy approximation. The hybrid technique used the rough set theory as a classifier and the lexicon-based as a vector. Furthermore, this study built three types of corpuses (V1, V2, and V3) collected from Twitter. The experimental findings show that among the proposed hybrid methods, the accuracy approximation was superior to the lower approximation with seed vector. It was also revealed that hybrid methods outperformed machine learning techniques in terms of efficiency. Moreover, the study recommends using an accuracy approximation method with seed vector to identify the polarity of the text.

Background. The Even language is among the endangered languages. The situation requires comprehensive research, recording and documentation of the Even language and culture. The research of the synonymic relations in the Even language will show the lexical-semantic development of the Even word, the stylistic features of the language. Purpose. The article is devoted to the study of synonyms in the Even folk texts. Materials and methods. Epic tales of the Evens of Okhotsk are used as a source of research. The main method of research is the descriptive one along with semantic analysis and elicitation methods. Results. The collected lexical material, distributed according to the parts of speech, reveals a numerical superiority of verbal synonyms in comparison with other groups of words. In the texts of the narrator N.G Mokrousov. synonyms serve as expressive means, have expressive load, are used in the description of the various phenomena, properties, actions, are applied with a view of preservation of a rhythm of singing. Frequent synonyms are recorded in the work. Practical implications. The results of the work can be applied in studies on the language and folklore of the Tungus-Manchur peoples.

Sentiment analysis (SA) has been an important focus of study in the fields of computational linguistics and data analysis for a decade. Recently, promising results have been achieved when applying DNN models to sentiment analysis tasks. Long short-term memory (LSTM) models, as well as its derivatives like gated recurrent unit (GRU), are becoming increasingly popular in neural architecture used for sentiment analysis. Using these models in the feature extraction layer of a DNN results in a high dimensional feature space, despite the fact that the models can handle sequences of arbitrary length. Another problem with these models is that they weight each feature equally. Natural language processing (NLP) makes use of word embeddings created with word2vec. For many NLP jobs, deep neural networks have become the method of choice. Traditional deep networks are not dependable in storing contextual information, so dealing with sequential data like text and sound was a nightmare for such networks. This research proposes multichannel word embedding and employing stack of neural networks with lexicon-based padding and attention mechanism (MCSNNLA) method for SA. Using convolution neural network (CNN), Bi-LSTM, and the attention process in mind, this approach to sentiment analysis is described. One embedding layer, two convolution layers with max-pooling, one LSTM layer, and two fully connected (FC) layers make up the proposed technique, which is tailored for sentence-level SA. To address the shortcomings of prior SA models for product reviews, the MCSNNLA model integrates the aforementioned sentiment lexicon with deep learning technologies. The MCSNNLA model combines the strengths of emotion lexicons with those of deep learning. To begin, the reviews are processed with the sentiment lexicon in order to enhance the sentiment features. The experimental findings show that the model has the potential to greatly improve text SA performance.

AbstractThis research aims to examine the ecological lexicon of the East Java community through a linguistic ecological approach. The focus of this study is to understand the vocabulary and ecological concepts used by the people of East Java in describing wildlife and their natural environment. The research is conducted by identifying and analyzing vocabulary related to flora and fauna, as well as ecological concepts present in the language and culture of East Java. Research methods used include field surveys, interviews, language data collection, and participatory observations. Data is collected through direct interactions with the people of East Java, including farmers, local residents, and community figures who possess knowledge and experience in interacting with wildlife and the natural environment. Data analysis is carried out using a linguistic ecological approach, which involves mapping ecological vocabulary, identifying distinct ecological concepts, and tracing the relationship between ecological vocabulary and local culture. The results of the research indicate that the people of East Java have a rich and unique vocabulary related to wildlife and their natural environment. This vocabulary reflects the diversity of wildlife in the region, as well as the close relationship between the community and the natural environment. Ecological concepts, such as local wisdom in natural resource management, protection of specific wildlife, and understanding the interconnectedness between humans and nature, are also found in the ecological lexicon of the East Java community. These findings have important implications for language and cultural development, as well as environmental conservation in East Java. Preserving local vocabulary can maintain the cultural richness and identity of the East Java community, while the use of ecological lexicon in education and environmental awareness can enhance the understanding and participation of the community in wildlife and habitat conservation. The findings of this research can also serve as a basis for developing more relevant conservation policies based on the understanding of the local community.

Abstract Background Patients’ rights are integral to medical ethics. This study aimed to perform sentiment analysis and opinion mining on patients’ messages by a combination of lexicon-based and machine learning methods to identify positive or negative comments and to determine the different ward and staff names mentioned in patients’ messages. Methods The level of satisfaction and observance of the rights of 250 service recipients of the hospital was evaluated through the related checklists by the evaluator. In total, 822 Persian messages, composed of 540 negative and 282 positive comments, were collected and labeled by the evaluator. Pre-processing was performed on the messages and followed by 2 feature vectors which were extracted from the messages, including the term frequency–inverse document frequency (TFIDF) vector and a combination of the multifeature (MF) (a lexicon-based method) and TFIDF (MF + TFIDF) vectors. Six feature selectors and 5 classifiers were used in this study. For the evaluations, 5-fold cross-validation with different metrics including area under the receiver operating characteristic curve (AUC), accuracy (ACC), F1 score, sensitivity (SEN), specificity (SPE) and Precision-Recall Curves (PRC) were reported. Message tag detection, which featured different hospital wards and identified staff names mentioned in the study patients’ messages, was implemented by the lexicon-based method. Results The best classifier was Multinomial Naïve Bayes in combination with MF + TFIDF feature vector and SelectFromModel (SFM) feature selection (ACC = 0.89 ± 0.03, AUC = 0.87 ± 0.03, F1 = 0.92 ± 0.03, SEN = 0.93 ± 0.04, and SPE = 0.82 ± 0.02, PRC-AUC = 0.97). Two methods of assessment by the evaluator and artificial intelligence as well as survey systems were compared. Conclusion Our results demonstrated that the lexicon-based method, in combination with machine learning classifiers, could extract sentiments in patients’ comments and classify them into positive and negative categories. We also developed an online survey system to analyze patients’ satisfaction in different wards and to remove conventional assessments by the evaluator.

In Belgium, as in other French-speaking countries, there has been a centuries-old purist tradition, focusing its anathemas on topolectal variation. The primacy of an exogenous norm (the French “from Paris”) was not challenged before the end of the 20th century. At present, the legitimacy of certain endogenous norms is acknowledged, particularly in the lexical field. We will outline the main stages of this evolution in the attitudes and representations of French-speaking Belgians and the opportunities which can be drawn from it for a better consideration of topolectal variation in the teaching of French.

Although human factors (e.g., cognitive functions, behaviors and skills, human error models, etc.) are key elements to improve software development productivity and quality, the role of software developers’ emotions and their personality traits in software engineering still needs to be studied. A major difficulty is in assessing developers’ emotions, leading to the classic problem of having difficulties understanding what cannot be easily measured. Existing approaches to infer emotions, such as facial expressions, self-assessed surveys, and biometric sensors, imply considerable intrusiveness on developers and tend to be used only during normal working periods. This article proposes to assess the feasibility of using social media posts (e.g., developers’ posts on Twitter) to accurately determine the polarity of emotions of software developers over extended periods in a non-intrusive manner, allowing the identification of potentially abnormal periods of negative or positive sentiments of developers that may affect software development productivity or software quality. Our results suggested that Twitter data can serve as a valid source for accurately inferring the polarity of emotions. We evaluated 31 combinations of unsupervised lexicon-based techniques using a dataset with 79,029 public posts from Twitter from sixteen software developers, achieving a macro F1-Score of 0.745 and 76.8% of accuracy with the ensemble comprised of SentiStrength, Sentilex-PT, and LIWC2015_PT lexicons. Among other results, we found a statistically significant difference in tweets’ polarities posted during working and non-working periods for 31.25% of the participants, suggesting that emotional polarity monitoring outside working hours could also be relevant. We also assessed the Big Five personality traits of the developers and preliminarily used them to ponder the polarities inferences. In this context, Openness, Conscientiousness, and Extraversion were frequently related to neutral and positive posts, while Neuroticism is associated with negative posts. Our results show that the proposed approach is accurate enough to constitute a simple and non-intrusive alternative to existing methods. Tools using this approach can be applied in real software development environments to support software team workers in making decisions to improve the software development process.

As the most recent historiography on Fascism has amply analysed, art and culture occupied an important place in the Fascist totalitarian project. Mussolini himself had a privileged relationship with writing, whether literary, poetic or journalistic. The aim of this paper is to analyse all the occurrences of ‘arte’ and ‘poesia’ (and their closest derivatives) and the contexts in which they are used throughout Benito Mussolini’s Opera omnia, in order to understand the meaning and political issues that these terms encompassed for him throughout his life and career. What emerges above all from this study is the fact that words such as ‘arte’ and ‘poesia’ are not used solely in the aesthetic sphere: Mussolini also used them to describe both his own politics and those of his opponents. During the socialist period, they were used to describe – and discredit – the discourse of his political opponents, but at the time of the Caporetto turning point, the lexical field of art was used in both a positive and metaphorical sense. On the one hand, Mussolini developed the metaphor of the political artist to define the political leader he intended to be for the Italians; on the other, he enhanced the idea of poetry as action while stripping the word of its literal meaning.

Resumo: No presente trabalho há um estudo conciso em Ciências do Léxico, em que é definido o conceito de léxico segundo a lexicóloga Maria Tereza Biderman e como se dá a dicionarização do léxico de acordo com a linguista Maria da Graça Krieger. Posteriormente, aborda-se uma breve história da produção lexicográfica e, logo após, os pressupostos da Lexicografia Pedagógica com o suporte do Programa Nacional do Livro Didático - Dicionários (2012) e da Base Nacional Comum Curricular (2017). Tal movimento tem o intuito de mostrar que, para além das contribuições no que tange à expansão do conhecimento vocabular e linguístico, os dicionários escolares também colaboram para a formação cidadã dos estudantes. Logo, os professores devem fazer uso desse instrumento levando em consideração as múltiplas possibilidades de ensino e aprendizagem que a materialidade discursiva das obras lexicográficas escolares proporciona, e que auxilia na formação e representação do aluno enquanto cidadão. Palavras-chaves: discurso; ensino; léxico; lexicografia. Abstract: In the present work there is a concise study in Lexicon Sciences, in which the concept of lexicon is defined according to the lexicologist Maria Tereza Biderman and how the lexicon is dictionarized according to the linguist Maria da Graça Krieger. Subsequently, a brief history of lexicographical production is approached and, soon after, the assumptions of Pedagogical Lexicography with the support of the National Textbook Program - Dictionaries (2012) and the National Common Curricular Base (2017). This movement aims to show that, in addition to the contributions regarding the expansion of vocabulary and linguistic knowledge, school dictionaries also collaborate for the citizenship education of students. Therefore, teachers must make use of this instrument, taking into account the multiple possibilities of teaching and learning that the discursive materiality of school lexicographical works provides, and which helps in the formation and representation of the student as a citizen. Keywords: discourse; lexicography; lexicon; teaching.

Background. Forming a system of spatial, social and cultural landmarks, each speaker consciously/unconsciously records proper names which seem important. The most significant units are remembered, and it is they that determine the general idea of the entire set of marked objects. Since the system of linguistic units in the individual mental lexicon is regulated by a great number of subjective factors, it can be assumed that the tendencies of the reflection of reality in the mental lexicon common to a group of speakers open the way to the analysis of current social stereotypes. Shop and store names are one of the groups of commercial names, therefore, by their very nature, they are maximally oriented towards reflecting positive stereotypes of large social groups. Purpose. The purpose of this article is to analyze how the names of shops and stores are reflected in the mental lexicon of the women residents of Kyiv, the capital of Ukraine, and to try to outline the connection between the proper names verbalization in speakers’ mental lexicon and their ideas about extralinguistic reality. Methods. The material for this study consists of 249 graphic variants of 160 names of clothing, footwear and food stores, collected by surveying 45 women residents of Kyiv. Descriptive, comparative, and quantitative methods were used in the research, and techniques of the structural method were occasionally involved. Results. Current store names in the capital of Ukraine create а very colorful linguistic landscape with its main feature – the predominance of foreign language components, both lexical and graphic. Among all this diversity, the speaker remembers 3 or 4 names оn average, which determine her idea of the general trends in the nomination of objects in this field and indirectly ‒ these objects themselves. The analysis of store and shop names active in the mental lexicon of Kyiv residents shows that the absolute majority of clothing and shoe stores (79 % and 81 %, respectively) are perceived by names identified with other cultural spaces. Not only the name’s origin, but primarily its graphic form is a clear indicator of belonging to some cultural space. The opposite case in the name system of grocery stores is recorded ‒ only 26 % of them were reproduced by respondents in Latin. The form in which the store or shop name is stored in the mental lexicon depends on a) the graphic code visualized on the signboard / in the advertisement and b) the sound form of the name commonly used in informal communication. The activity of the second factor directly depends on the symmetry of the sound and spelling of the barbarism name and the level of speaker’s foreign language competence. The result of the collision of different graphic codes in the speaker’s mind is mixing, which is manifested in the recording of the original form of the name from Latin to Cyrillic during memorization. Therefore, while keeping proper names in memory, speakers try to assimilate their form to the rest of the fixed units, and this often manifests itself in the transformation of the original form of proper name. Discussion. Oversaturation of Kyiv’s commercial ergonomics system with barbaric names forms a strong public stereotype about the attractiveness and progressiveness of other cultures in the consumption sphere and creates the illusion of the absence of national Ukrainian in it. Trying to master the system of store and shop names, Kyiv residents find themselves in a conflict situation: the dominant graphic code for them is the Cyrillic alphabet, while the Latin alphabet prevails in the visual space of Kyiv’s trade establishments. The way out of this situation is transformation ‒ recording of the original name with the help of a graphic system convenient for the speaker. In order to form a general idea about the reflection of the commercial proper names system in the mental lexicon of Ukrainians, it is necessary to involve in the study data from representatives of different age groups from different regions of the country.

In the early period of the Republic of Turkey, sports clubs played a critical role in the promotion of sports in the public sphere, particularly less widespread sports, and the transformation of sporting activities into recreational leisure activities. This was all done in line with the physical training policies of the state. During this period, Ankara sports clubs introduced different qualities to modern leisure activities within new ‘locales', and so played an active role in the transformation of urban space. They did this through the use of recreational leisure activities to emphasise a sense of belonging, entertainment, and recreation amongst the citizens. This study considers the sporting events, as well as the locales where they took place, that were organized by sport clubs in Ankara, the new capital. The period considered begins in 1922, when the institutionalization of sports began with the formation of The Turkish Alliance of Associations Promoting Exercise, until 1946 when the sporting activities were more comprehensively organised. Analysis of the transformation of sports activities into recreational leisure activities, as well as the role of sports clubs in redefining daily life and urban space, considers a variety, in terms of scales and qualities, of activities and locales. The Ankara daily newspaper Hakimiyet-i Milliye [which was renamed Ulus in 1934), was the main primary source used in this study, although certain weekly magazines, such as Resimli Uyanış, (Servet-i Fünun) and Gol Spor, were used to obtain further information and analysis of events and locations.

Purpose – Twitter is the most widely used platform with an open network; hence, tourists often resort to Twitter to share their travel experiences, satisfaction/dissatisfaction and other opinions. This study is divided into two sections, first to provide a framework for understanding public sentiments through Twitter for tourism insights, second to provide real-time insights of three Indian heritage sites i.e., the Taj Mahal, Red Fort and Golden Temple by extracting 5,000 tweets each (n = 15,000) using Twitter API. Results are interpreted using NRC emotion lexicon and data visualisation using R. Design/methodology/approach – This study attempts to understand the public sentiment on three globally acclaimed Indian heritage sites, i.e. the Taj Mahal, Red Fort and Golden temple using a step-by-step approach, hence proposing a framework using Twitter analytics. Extensive use of various packages of R programming from the libraries has been done for various purposes such as extraction, processing and analysing the data from Twitter. A total of 15,000 tweets from January 2015 to January 2021 were collected of the three sites using different key words. An exploratory design and data visualisation technique has been used to interpret results. Findings – After data processing, 12,409 sentiments are extracted. Amongst the three tourists' spots, the greatest number of positive sentiments is for the Taj Mahal and Golden temple with approximately 25% each. While the most negative sentiment can be seen for the Red Fort (17%). Amongst the positive emotions, the maximum joy sentiment (12%) can be seen in the Golden Temple and trust (21%) in the Red Fort. In terms of negative emotions, fear (13%) can be seen in the Red fort. Overall, India's heritage sites have a positive sentiment (20%), which surpasses the negative sentiment (13%). And can be said that the overall polarity is towards positive. Originality/value – This study provides a framework on how to use Twitter for tourism insights through text mining public sentiments and provides real- time insights from famous Indian heritage sites.

Recent work argues that a bilingual linguistic system is fully integrated in one competence system and does not consist of two separate, autonomous systems as is commonly assumed (see Goldrick et al 2016, Grimstad et al 2014, López 2020, Riksam 2017). Here, we explore the organization of the lexicon within the integration hypothesis using data based on idioms and code-switching. The working hypothesis is that if the lexicons of a bilingual person are integrated in the sort of grammatical architecture presented in López (2020), one should be able to code-switch within the idiom and retain the idiomatic meaning. After a pilot study with a community of Papiamentu-Dutch bilinguals, we tested this hypothesis with two communities of bilingual code-switchers: Basque-Spanish, English-Spanish. The task consisted of choosing a meaning out of three choices for a range of sentences, some of which included code-switched idioms. Our results, by-and-large, confirm the hypothesis that code-switching does not destroy the integrity of the idiom.

With a millennium-long history, traditional Chinese cereal vinegar (CCV) is a significant part of China’s cultural heritage. The unique flavor of CCV is derived from the use of cereal and its bran as raw materials and solid-state fermentation as a brewing technique. This paper systemically summarized recent research progress on the aroma compounds in CCV, the biochemical generation of aroma compounds during the brewing process, and the association between sensory perception and the primary aroma compounds. Furthermore, a complete CCV lexicon and sensory wheel prototype were constructed. This study aims to lay a foundation for future CCV aroma research, quality improvement, and industrialization.

This article provides information about the onomastics field of linguistics and the anthroponyms included in it. The article describes in detail the gradual study of Uzbek language antoponyms by Turkological scientists and their work on anthroponyms. Not only Uzbek linguists, but also world linguists’ researches in this field are described in the article.Proper use of the form of an anthroponym, knowledge of a foreign language and knowledge of foreign cultural models of personal names are one of the most important conditions for the success of the process of intercultural communication. Many issues related to the functioning of personal names have been addressed by various disciplines.Anthroponyms are of great importance in people's lives. They reflected the culture and worldview of society. Names are inextricably linked with the history of the people. This article focuses on lexical-semantic, their origin and etymological research of anthroponyms in Uzbek and Russian languages.

Taste sensitivity can have a significant impact on consumers’ food choices. Consumers’ taster status and emotions can be guided by sensory information of sugared products. This paper aimed to develop emotional lexicons for sugar-free chocolates based on consumers’ taster status applying the check-all-that-apply (CATA) methodology. South African respondents’ (n = 153) bitter perception was evaluated with n-propylthiouracil (PROP) paper strips. Respondents received one sugar-free dark chocolate and one sugar-free milk chocolate and completed an electronic questionnaire. Respondents mainly purchased chocolate for its flavour, and enjoyed the taste of the sugar-free dark chocolate more than sugar-free milk chocolate. The non-tasters (>50%) chose positive emotions for sugar-free milk chocolate, while the medium tasters, selected more positive emotions for dark chocolate. The supertasters selected the most negative emotions for the sugar-free dark chocolate. Practical significant associations were found between the non-tasters and the emotion guilty, as well as between the supertasters and the emotions, discontented and disgust. Each taster status requires the development of a distinctive lexicon to be emotionally satisfied by sugar-free products.

This study investigates the relationships between lexical development and inhibition, as well as morphosyntax and inhibition, in typically developing monolingual Spanish-speaking children. Recent studies of the relationship between lexical development and inhibition suggest that, as the size of the lexicon increases, so does inhibitory ability. However, the relationship between grammar and inhibition seems more controversial. The work distinguishing the relationships between inhibition and lexicon vs. grammar have been carried out in English, which has relatively impoverished inflectional morphology. Because the relationships considered in the literature are hypothetically not language-particular to English, but rather claims about cognition in general, we would expect to find that they also hold in other languages, including languages with richer morphology, such as Spanish. These considerations led us to ask the following: are expressive and receptive measures of the lexicon and morphosyntax predictive of typically developing monolingual child Spanish-speakers’ inhibitory ability? A sample of 82 monolingual, typically developing Spanish-speaking children in Mexico City were tested with 5 lexical measures, 4 morphosyntax measures, and the Flanker Task measure of inhibition. Results showed that all lexical and morphosyntactic variables correlated significantly with Flanker (p < 0.01), except for Number of Different Words (NDW), calculated on the spontaneous production sample. Therefore, inhibition is predicted by lexical development in child Spanish. Additionally, an ever-increasing set of competitor morphological forms requires an ever-increasing inhibitory ability as well.

This research highlights the importance of the Arabic lexicon in teaching and studying ta’bîr courses in Ma’had al-Imarat Bandung. This qualitative research depends on a field study and a descriptive analysis. This importance is due to three aspects: The first is the ta’bîr courses of materials prescribed in any Arabic language learning institutes to develop students’ four skills. The second is that lexicons are tools for teaching and learning the Arabic language, especially in the subject matter of ta’bîr. The third is that the Arabic lexicon is one of the primary sources people refer to correct their linguistic knowledge. The results indicate that language acquisition is the most important of that knowledge. Furthermore, in acquiring the Arabic language, many factors are linguistic and non-linguistic. Dictionaries are considered one of the primary tools in language acquisition in studying the subject matter of ta’bîr.

IntroductionMany words are categorially ambiguous and can be used as a verb (to paint) or as a noun (the paint) due to the presence of unpronounced morphology or “zero morphology”. On this account, the verb “paint” is derived from the noun “paint” through the addition of a silent category-changing morpheme. Past studies have uncovered the syntactic and semantic properties of these categorially ambiguous words, but no research has been conducted on how people process them during normal or impaired lexical processing. Are these two different uses of “paint” processed in the same way? Does this morphosyntactic structure have an effect on online sentence processing?MethodsThis study presents two experiments that investigate the effect of morphosyntactic complexity in categorially ambiguous words presented in isolation (experiment 1) and in a sentential context (experiment 2). The first experiment tested the ability to process categorially unambiguous and ambiguous nouns and verbs in 30 healthy older adults and 12 individuals with aphasia, using a forced choice phrasal-completion task, in which individuals choose whether the or to is most compatible with target words.ResultsHealthy controls and individuals with fluent aphasia all showed: (1) a bias toward the base category in selection rates for the and to, where the was selected more frequently for words identified to be base nouns, and to was selected more frequently for base verbs, and (2) longer reaction times for ambiguous (over unambiguous) words. However, individuals with non-fluent agrammatic aphasia showed a base-category effect only for nouns, with chance performance for verbs. The second experiment, using an eye-tracking while reading paradigm with 56 young healthy adults, showed a reading time slowdown for derived forms (to paint) compared to their base-category counterparts (the paint) in sentence contexts.DiscussionThese findings suggest that categorially ambiguous words likely share a common root, and are related by zero-derivation, and that impaired access to the base-category (i.e., verbs like to visit) precludes associated morphological processes and therefore the retrieval of the derived-category (i.e., nouns like the visit) in non-fluent agrammatic aphasia. This study provides insights into the theory of zero morphology, and the principles that need to be accounted for in models of the lexicon.

Languages change over time, driven by creation of new words and cultural pressure to optimize communication. Programming languages resemble written language but communicate primarily with computer hardware rather than a human audience. I tested whether there were detectable changes over time in use of R, a mature, open-source programming language used for scientific computing. Across 393 142 GitHub repositories published between 2014 and 2021, I extracted 143 409 288 R functions, programming ‘verbs’, pairing linguistic and ecological analyses to detect change to diversity and composition of functions used over time. I found the number of R functions in use increased and underwent substantial change, driven primarily by the popularity of the ‘tidyverse' collection of community-written extensions. I provide evidence that users can change the nature of programming languages, with patterns that match known processes from natural languages and genetic evolution. In R, there appear to be selective pressures for increased analytic complexity and R functions in decline that are not yet extinct (extinction debts). R's evolution towards the tidyverse may also represent the start of a division into two distinct dialects, which may impact the readability and continuity of analytic and scientific inquiries codified in R, as well as the language's future.

In this paper, two techniques for sentiment classification are proposed: Gujarati Lexicon Sentiment Analysis (GLSA) and Gujarati Machine Learning Sentiment Analysis (GMLSA) for sentiment classification of Gujarati text film reviews. Five different datasets were produced to validate the machine learning-based and lexicon-based methods’ accuracy. The lexicon-based approach employs a sentiment lexicon known as GujSentiWordNet, which identifies sentiments with a sentiment score for feature generation, while in the machine learning-based approach, five classifiers are used: logistic regression (LR), random forest (RF), k-nearest neighbors (KNN), support vector machine (SVM), naive Bayes (NB) with TF-IDF, and count vectorizer for feature selection. Experiments were carried out and the results obtained were compared using accuracy, precision, recall, and F-score as performance evaluation criteria. According to the test results, the machine learning-based technique improved accuracy by 3 to 10% on average when compared to the lexicon-based approach.

Measuring people's life satisfaction in real time on a large scale is quite valuable for monitoring and promoting public mental health; however, the traditional questionnaire method cannot fully meet this need. This study utilized the emotion words in self-statement texts to train machine learning predictive models to identify an individual's life satisfaction. The SVR model was found to have the best performance, with the correlation between predicted scores and self-reported questionnaire scores achieving 0.42 and the split-half reliability achieving 0.939. This result demonstrates the possibility of identifying life satisfaction through emotional expressions and provides a method to measure the public's life satisfaction online. The word categories selected through the modeling process were happy (PA), sorrow (NB), boredom (NE), reproach (NN), glad (MH), aversion (ME), and N (negation + positive), which reveal the specific emotions in self-expression relevant to life satisfaction.

This study examines the role and place of youth media in changing the vocabulary of the Russian language. For a comparative analysis, three words were used, the factors of popularity of which are political propaganda, the frequent use of the word in a certain youth magazine and the widespread prevalence of the word on the Internet. A wave-like dynamics of an increase in the frequency of the word, which has become popular thanks to publications in the youth media, has been revealed: matured readers of the magazine, after 20-25 years, begin to actively use the word introduced into their vocabulary by the authors of the publications. The question is raised about the significance of the mass media for the dynamics of changes in the vocabulary of the language. A method has been developed to prove the influence of the mass media on the dynamics of changes in the vocabulary using the tools of quantitative linguistics. The history of the frequency of use of the analyzed words in the Russian language allows us to speak about the importance of youth mass media as determining the worldview and linguistic picture of the world of the text. Moreover, for other words in which the frequency correlates with the historical setting, the contexts of use themselves indicate the connection of the increased frequency with the personality of a particular publicist or writer and with the texts he generates.

The purpose of this dataset is to collate average word lengths in Greek in the Classical period (using a sample from the 5th century BCE) and the average word lengths in the Post-classical period (using a sample from the 1st century CE). This dataset, which is stored as a CSV file in the Harvard Dataverse, has been used to demonstrate that the average length of words in Greek increased significantly between the Classical and Post-classical periods. It comprises two word lists and corresponding word lengths for each sample; a table of the average word lengths (for nouns, adjectives, verbs, adverbs, and total) of each sample and the statistical t-test results showing the significance of the difference in word lengths between Classical and Post-classical Greek. This dataset has a reuse potential for linguists investigating diachronic change in word lengths as well as for historical linguists looking at the evolution of Classical and Post-classical Greek.

Social media users use words and phrases to convey their views or opinions. However, some people use idioms or proverbs that are implicit and indirect to make a stronger impression on the audience or perhaps catch their attention by utilizing funny, sarcastic, or metaphorical phrases. Idioms and proverbs are figurative expressions with a thematically coherent totality that cannot be understood literally. In previous work, the extension of IBM’s Sentiment Lexicon of Idiomatic Expressions was proposed to include around 9,000 idioms; a crowdsourcing service manually annotates both lexicons. Therefore, in this research, we provide a knowledge-based expansion approach to avoid human annotation of idioms. For sentiment classification, the proposed method has the advantage that it does not require any fine-tuning for the BERT model. Experimental comparisons show that automated idiom enrichment and annotation are very beneficial for the performance of the sentiment classifier. The expanded annotated lexicon will be made available to the general public.

There is the minimal restriction to users’ speech in cyberspace. The Internet provides a space where people can freely present their speech, which puts a Utopian sense of freedom of speech into practice. However, the appearance of hate speech is a significant side effect of online freedom of speech. Some users use hate speech to attack others, making the attacked targets uncomfortable. The proliferation of hate speech poses severe challenges to cyber society. Users may hope that social media platforms and online communities promote anti-hate speech. However, hate speech detection is still a developing technology that requires system developers to create a method to detect unacceptable hate speech while maintaining the online freedom of speech environment. No excellence detection approach has yet been proposed, although some literature has focused on it. The current study proposes an approach to build a political hate speech lexicon and train artificial intelligence classifiers to detect hate speech. Our academic and practical contributions include the collection of a Chinese hate speech dataset, creating a Chinese hate speech lexicon, and developing both a deep learning-based and a lexicon-based approach to detect Chinese hate speech. Although we focus on Chinese hate speech detection, our proposed hate speech detection system and hate speech lexicon development approach can also be used for other languages.

Orientation: Meaning is not a concept whose significance needs to be debated anymore. Rather, the meaning of meaning is a concept that needs more clarity to improve its understanding. Research purpose: In this paper, the construct of meaning is deconstructed to develop a lexicon of the respective meanings of meaning, especially as they apply to the domain of work. Motivation for the study: Descriptions of the various meanings of meaning tend to be lost across many different journal articles and books. More clarity regarding the meanings of meaning and how they compare and relate with each other is essential to promote valid research and influential practice in this field. Research approach/design and method: Theoretical research is conducted through a literature study and the meanings of meaning are determined through theory synthesis and topical analyses. Main findings: Meaning is a multidimensional construct, especially as it applies to the work context. The concept of meaning in life is distinct and should be distinguished from related concepts, such as the meaning of work, meaning at work, meaning in work, and meaningful work. Practical/managerial implications: By clarifying meanings of meaning, the lexicon provides a unique reference work for scholars, and an essential guide for practitioners in the fields of psychology, industrial and organisational psychology, and even psychiatry, who aspire to advance and promote meaningfulness in their work contexts. Contribution/value-add: As far as could be established, this is the first lexicon of the meanings of meaning in one easy-to-use compendium, for accurate comparison and reference.

Corpus linguistics (i.e. research on language based on written or oral linguistic material that has been collected and saved) has been considerably developed over the last decades. This development has occurred using more numerous and larger corpora. The increased size of corpora has required the development of automatic tools for their analysis, but also a real reflection on the nature and the objectives of the annotation of corpora. The increased size of the corpora has required the development of automatic tools for their analysis, but also a real reflection on the nature and the objectives of the annotation of the corpora. The enrichment of corpora by a set of specific annotations has emerged, in most cases, as a preliminary to any linguistic analysis.Annotating a corpus consists in adding relevant information for its exploitation. The interest of having annotated corpora (i.e. enriched at different linguistic levels) is to be able to study each annotated levels and the mutual links between them. The work carried out at the LPL on these issues of corpus enrichment was initially meant to make possible the study of multimodality, such as the finest levels of granularity (phonemes) up to the mimo-gestural levels, passing through the syntactic, discursive, prosodic, and interactional levels. It was therefore necessary to think about annotation early on, at the level of information representation. A global annotation scheme allows to consider all these levels in a single formal approach that facilitates their subsequent interrogation.Whatever the level of annotation, several questions have arisen: on the one hand there were questions about the labels used (e.g. decomposition, typology, function, gradual/categorical nature); on the other hand there were questions about the temporary embedment of these labels (location and boundaries). For certain levels of annotation, it will be necessary to describe the levels of dependence between the different labels. These questions must be considered in relation to the research objectives. The work within each annotation level is then relatively similar. It is a question of establishing an annotation scheme that allows the most consistent and robust annotation possible. This scheme is established based on theoretical knowledge and in order to answer research questions. Once the annotation scheme is established, it is also possible to build an annotation guide for potential annotators (expert/naive). Most often, annotations are performed using several annotators to make possible an evaluation of the consistency (inter-annotator agreements). The transversal issue of heterogeneity in human annotations will be addressed in this chapter.In this chapter, we develop some of the main annotation steps that have been performed to annotate corpora manually or automatically, as well as the research issues associated with them. These steps are listed below: - Automatic search of IPUs and orthographic transcriptionFrom the collected primary data, we automatically search for IPUs - Inter-Pausal Units - which allow us to obtain a segmentation into silence blocks versus sound blocks. We then perform the orthographic transcription within these IPUs. This transcription step is crucial as it constitutes the tier from which the other annotation levels will be developed. Here again, the choices made in terms of transcription (chosen convention) have an impact on the links between annotation levels. Once the orthographic transcription is done - and aligned with the signal on IPUs - many annotations can be obtained, either manually, automatically, or semi-automatically. - Phonetic and lexical annotationWe develop, distribute, and regularly enrich an automatic annotation software -SPPAS, which also allows to normalize the transcribed text, which means to obtain the tokens. From these tokens within the IPUs, SPPAS can perform the grapheme-phoneme conversion based on a grammar of the possible pronunciations of each IPU. Finally, SPPAS provides the temporal alignment of phonemes which is now rarely performed manually. However, the manual and automatic aspects of phonetic annotation are different but complementary processes. Thus, spontaneous speech generates phonetic realizations (reductions) that are difficult to manage at the level of automatic alignment. Consequently 1/it may be necessary to manually correct some parts of the automatic alignment: 2/it is possible to use the alignment errors to locate these specific phonetic realizations. In this chapter, we will address the issues related to these two aspects. Other annotations can then be obtained from this phoneme segmentation. They allow to automatically obtain the alignment of tokens; a rule-based system allows to group phonemes into syllables. - Syntactic annotationSyntactic annotation is based on tokens. If there are automatic syntactic analyzers available for written language, syntactic analysis of spoken French remains a challenge. We present here the methodology we have adopted to adapt our writing tagger to handle spontaneous spoken transcripts. If the performances of our MarsaTag tagger are already acceptable, the improvement of our tool will require a multi-level modeling including the phenomena of disfluencies (see below) and the more precise treatment of discourse markers. - Annotation of disfluenciesOral utterances contain many variations in verbal fluency at several levels (e.g. the rate of pronunciation of words, phrases, or clauses). But these variations can also occur at the acoustic and phonetic levels. On the morphological and syntactic levels, some of these variations are translated by real self-interruptions which suspend the syntagmatic flow in the verbal emission. In our corpus analyses, we have planned to keep (in addition to filled or unfilled pauses, discourse elements, interjections) the evidence of the discourse elaboration which are, among other things, initiations or fragments of words and the syntagms’ breaks. This strategy made it possible to envisage a detailed and exhaustive description of these phenomena designated under the term of “disfluency”. - Annotation of speech and interactionsFrom the speech signal and its transcription, it is also possible to consider an annotation of several pragmatic levels such as the thematic organization of conversational interactions. Several levels of annotation will be described in this chapter: the annotation of conversational themes, thematic transitions (i.e. conversational movements that allow to go from one topic to another), and the phases of these transitions. Other phenomena will also be described, such as feedback items and humorous sequences. We will present the annotation protocol associated with these different phenomena as well as the evaluation methods chosen to assess the reliability of these annotations. - Mimogestual annotation From the video signal, it is possible to consider a mimogestual annotation (facial expressions or coverbal manual gestures for example). This can be done either manually or semi-automatically. In this chapter, first we will present the semi-automatic annotation protocol of smiles that we have developed in order to annotate two conversational corpora. We will present the SMAD tool which allows to automatically annotate smiles. Then, we will describe the protocol of correction of these annotations. Finally, we will discuss the evaluation method chosen to assess the robustness of the annotated data. We will also present the manual annotation of coverbal gestures as well as the inherent methodological issues such as annotation schemes and guides, typologies and segmentation. We will give examples of studies carried out at LPL that propose different approaches for gesture annotation.

Тюркские заимствования в даргинском языке составляют весьма обширный пласт его лексического состава. Тюркизмы пришли в даргинский язык из разных тюркских языков или напрямую, или опосредованно (через персидский и арабский). Тематически тюркизмы охватывают все сферы жизни. В статье рассматриваются вопросы определения кумыкского пласта в тюркских заимствованиях даргинского языка. Актуальность статьи определяется неисследованностью проблемы определения кумыкских заимствований в даргинском языке. Научная новизна исследования заключается в том, что впервые проводится комплексный анализ тюркских заимствований в даргинском языке и выделяется в нем кумыкский пласт. Основное содержание исследования составляет анализ структурно-семантических особенностей кумыкских заимствований и их адаптация в даргинском языке.