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Classical null hypothesis significance tests are not appropriate in corpus linguistics, because the randomness assumption underlying these testing procedures is not fulfilled. Nevertheless, there are numerous scenarios where it would be beneficial to have some kind of test in order to judge the relevance of a result (e.g. a difference between two corpora) by answering the question whether the attribute of interest is pronounced enough to warrant the conclusion that it is substantial and not due to chance. In this paper, I outline such a test. [ABSTRACT FROM AUTHOR]

We learn language from our social environment. In general, the more sources we have, the less informative each of them is, and the less weight we should assign it. If this is the case, people who interact with fewer others should be more susceptible to the influence of each of their interlocutors. This paper tests whether indeed people who interact with fewer other people have more malleable phonological representations. Using a perceptual learning paradigm, this paper shows that individuals who regularly interact with fewer others are more likely to change their boundary between /d/ and /t/ following exposure to an atypical speaker. It further shows that the effect of number of interlocutors is not due to differences in ability to learn the speaker’s speech patterns, but specific to likelihood of generalizing the learned pattern. These results have implications for both language learning and language change, as they suggest that individuals with smaller social networks might play an important role in propagating linguistic changes. [ABSTRACT FROM AUTHOR]

In order to demonstrate why it is important to correctly account for the (serial dependent) structure of temporal data, we document an apparently spectacular relationship between population size and lexical diversity: for five out of seven investigated languages, there is a strong relationship between population size and lexical diversity of the primary language in this country. We show that this relationship is the result of a misspecified model that does not consider the temporal aspect of the data by presenting a similar but nonsensical relationship between the global annual mean sea level and lexical diversity. Given the fact that in the recent past, several studies were published that present surprising links between different economic, cultural, political and (socio-)demographical variables on the one hand and cultural or linguistic characteristics on the other hand, but seem to suffer from exactly this problem, we explain the cause of the misspecification and show that it has profound consequences. We demonstrate how simple transformation of the time series can often solve problems of this type and argue that the evaluation of the plausibility of a relationship is important in this context. We hope that our paper will help both researchers and reviewers to understand why it is important to use special models for the analysis of data with a natural temporal ordering. [ABSTRACT FROM AUTHOR]

The expansion of the human species out of Africa in the Pleistocene, and the subsequent development of agriculture in the Holocene, resulted in waves of linguistic diversification and replacement across the planet. Analogous to the growth of populations or the speciation of biological organisms, languages diversify over time to form phylogenies of language families. However, the dynamics of this diversification process are unclear. Bayesian methods applied to lexical and phonetic data have created dated linguistic phylogenies for 18 language families encompassing ~3,000 of the world’s ~7,000 extant languages. In this paper we use these phylogenies to quantify how fast languages expand and diversify through time both within and across language families. The overall diversification rate of languages in our sample is ~0.001 yr-1 (or a doubling time of ~700 yr) over the last 6,000 years with evidence for nonlinear dynamics in language diversification rates over time, where both within and across language families, diversity initially increases rapidly and then slows. The expansion, evolution, and diversification of languages as they spread around the planet was a non-constant process. [ABSTRACT FROM AUTHOR]

Successful open source software (OSS) projects comprise freely observable, task-oriented social networks with hundreds or thousands of participants and large amounts of (textual and technical) discussion. The sheer volume of interactions and participants makes it challenging for participants to find relevant tasks, discussions and people. Tagging (e.g., @AmySmith) is a socio-technical practice that enables more focused discussion. By tagging important and relevant people, discussions can be advanced more effectively. However, for all but a few insiders, it can be difficult to identify important and/or relevant people. In this paper we study tagging in OSS projects from a socio-linguistics perspective. First we argue that textual content per se reveals a great deal about the status and identity of who is speaking and who is being addressed. Next, we suggest that this phenomenon can be usefully modeled using modern deep-learning methods. Finally, we illustrate the value of these approaches with tools that could assist people to find the important and relevant people for a discussion. [ABSTRACT FROM AUTHOR]

In this paper, we present a production study to explore the controversial question about /l/ velarisation. Measurements of first (F1), second (F2) and third (F3) formant frequencies and the slope of F2 were analysed to clarify the /l/ velarisation behaviour in European Portuguese (EP). The acoustic data were collected from ten EP speakers, producing trisyllabic words with paroxytone stress pattern, with the liquid consonant at the middle of the word in onset, complex onset and coda positions. Results suggested that /l/ is produced on a continuum in EP. The consistently low F2 indicates that /l/ is velarised in all syllable positions, but variation especially in F1 and F3 revealed that /l/ could be “more velarised” or “less velarised” dependent on syllable positions and vowel contexts. These findings suggest that it is important to consider different acoustic measures to better understand /l/ velarisation in EP. [ABSTRACT FROM AUTHOR]

Land reclamation has become a significant way for the improvement of ecological environment in mining areas. When selecting the optimal land reclamation scheme, LNNs (linguistic neutrosophic numbers) are suitable to describe the complex fuzzy evaluation information through linguistic truth, indeterminacy and falsity membership degrees. Furthermore, the Hamacher aggregation operators are good tools to handle multi-criteria decision making problems. Accordingly, the aim of this paper is to extend Hamacher aggregation operators with LNNs and then build a decision making framework for evaluating land reclamation schemes in mining areas. First, new operational laws of LNNs based on Hamacher t-norm and t-conorm are defined. Then, several linguistic neutrosophic Hamacher aggregation operators, including the linguistic neutrosophic Hamacher weighted mean aggregation operators and linguistic neutrosophic Hamacher hybrid weighted mean aggregation operators are developed. Meanwhile, their desirable properties are proved. Thereafter, a method for decision making with linguistic neutrosophic information based on these operators is proposed to deal with complex decision problems. At last, the validity of this method is confirmed by an illustrative example of evaluating the land reclamation schemes in mining areas. In addition, the impact of the parameter in extended Hamacher aggregation operators is discussed. The merits of the proposed method are also highlighted by comparing with other decision making methods. The results show that the proposed linguistic neutrosophic Hamacher aggregation operators have great flexibility and advantages, and can provide powerful ways for the evaluation of land reclamation schemes. [ABSTRACT FROM AUTHOR]

Computer-mediated communication is driving fundamental changes in the nature of written language. We investigate these changes by statistical analysis of a dataset comprising 107 million Twitter messages (authored by 2.7 million unique user accounts). Using a latent vector autoregressive model to aggregate across thousands of words, we identify high-level patterns in diffusion of linguistic change over the United States. Our model is robust to unpredictable changes in Twitter's sampling rate, and provides a probabilistic characterization of the relationship of macro-scale linguistic influence to a set of demographic and geographic predictors. The results of this analysis offer support for prior arguments that focus on geographical proximity and population size. However, demographic similarity – especially with regard to race – plays an even more central role, as cities with similar racial demographics are far more likely to share linguistic influence. Rather than moving towards a single unified “netspeak” dialect, language evolution in computer-mediated communication reproduces existing fault lines in spoken American English. [ABSTRACT FROM AUTHOR]

Forecasting extremely rare events is a pressing problem, but efforts to model such outcomes are often limited by the presence of multiple causes within classes of events, insufficient observations of the outcome to assess fit, and biased estimates due to insufficient observations of the outcome. We introduce a novel approach for analyzing rare event data that addresses these challenges by turning attention to the conditions under which rare outcomes do not occur. We detail how configurational methods can be used to identify conditions or sets of conditions that would preclude the occurrence of a rare outcome. Results from Monte Carlo experiments show that our approach can be used to systematically preclude up to 78.6% of observations, and application to ground-truth data coupled with a bootstrap inferential test illustrates how our approach can also yield novel substantive insights that are obscured by standard statistical analyses. [ABSTRACT FROM AUTHOR]

Twitter was an integral part of Donald Trump’s communication platform during his 2016 campaign. Although its topical content has been examined by researchers and the media, we know relatively little about the style of the language used on the account or how this style changed over time. In this study, we present the first detailed description of stylistic variation on the Trump Twitter account based on a multivariate analysis of grammatical co-occurrence patterns in tweets posted between 2009 and 2018. We identify four general patterns of stylistic variation, which we interpret as representing the degree of conversational, campaigning, engaged, and advisory discourse. We then track how the use of these four styles changed over time, focusing on the period around the campaign, showing that the style of tweets shifts systematically depending on the communicative goals of Trump and his team. Based on these results, we propose a series of hypotheses about how the Trump campaign used social media during the 2016 elections. [ABSTRACT FROM AUTHOR]

Like the transfer of genetic variation through gene flow, language changes constantly as a result of its use in human interaction. Contact between speakers is most likely to happen when they are close in space, time, and social setting. Here, we investigated the role of geographical configuration in this process by studying linguistic diversity in Japan, which comprises a large connected mainland (less isolation, more potential contact) and smaller island clusters of the Ryukyuan archipelago (more isolation, less potential contact). We quantified linguistic diversity using dialectometric methods, and performed regression analyses to assess the extent to which distance in space and time predict contemporary linguistic diversity. We found that language diversity in general increases as geographic distance increases and as time passes—as with biodiversity. Moreover, we found that (I) for mainland languages, linguistic diversity is most strongly related to geographic distance—a so-called isolation-by-distance pattern, and that (II) for island languages, linguistic diversity reflects the time since varieties separated and diverged—an isolation-by-colonisation pattern. Together, these results confirm previous findings that (linguistic) diversity is shaped by distance, but also goes beyond this by demonstrating the critical role of geographic configuration. [ABSTRACT FROM AUTHOR]

Fat talk and citizen science: Fat talk is a spontaneous verbal interaction in which interlocutors make self-disparaging comments about the body, usually as a request for assessment. Fat talk often reflects concerns about the self that stem from broader sociocultural factors. It is therefore an important target for sociocultural linguistics. However, real-time studies of fat talk are uncommon due to the resource and time burdens required to capture these fleeting utterances. This limits the scope of data produced using standard sociolinguistic methods. Citizen science may alleviate these burdens by producing a scale of social observation not afforded via traditional methods. Here we present a proof-of-concept for a novel methodology, citizen sociolinguistics. This research approach involves collaborations with citizen researchers to capture forms of conversational data that are typically inaccessible, including fat talk. Aims and outcomes: This study had two primary aims. Aim 1 focused on scientific output, testing a novel research strategy wherein citizen sociolinguists captured fat talk data in a diverse metropolitan region (Southwestern United States). Results confirm that citizen sociolinguistic research teams captured forms of fat talk that mirrored the scripted responses previously reported. However, they also capture unique forms of fat talk, likely due to greater diversity in sample and sampling environments. Aim 2 focused on the method itself via reflective exercises shared by the citizen sociolinguists throughout the project. In addition to confirming that the citizen sociolinguistic method produces reliable, scientifically valid data, we contend that citizen sociolinguist inclusion has broader scientific benefits which include applied scientific training, fostering sustained relationships between professional researchers and the public, and producing novel, meaningful scientific output that advances professional discourse. [ABSTRACT FROM AUTHOR]

Recently, emergence of signaling conventions, among which language is a prime example, draws a considerable interdisciplinary interest ranging from game theory, to robotics to evolutionary linguistics. Such a wide spectrum of research is based on much different assumptions and methodologies, but complexity of the problem precludes formulation of a unifying and commonly accepted explanation. We examine formation of signaling conventions in a framework of a multi-agent reinforcement learning model. When the network of interactions between agents is a complete graph or a sufficiently dense random graph, a global consensus is typically reached with the emerging language being a nearly unique object-word mapping or containing some synonyms and homonyms. On finite-dimensional lattices, the model gets trapped in disordered configurations with a local consensus only. Such a trapping can be avoided by introducing a population renewal, which in the presence of superlinear reinforcement restores an ordinary surface-tension driven coarsening and considerably enhances formation of efficient signaling. [ABSTRACT FROM AUTHOR]

We analyze the model of social interactions with coevolution of the topology and states of the nodes. This model can be interpreted as a model of language change. We propose different rewiring mechanisms and perform numerical simulations for each. Obtained results are compared with the empirical data gathered from two online databases and anthropological study of Solomon Islands. We study the behavior of the number of languages for different system sizes and we find that only local rewiring, i.e. triadic closure, is capable of reproducing results for the empirical data in a qualitative manner. Furthermore, we cancel the contradiction between previous models and the Solomon Islands case. Our results demonstrate the importance of the topology of the network, and the rewiring mechanism in the process of language change. [ABSTRACT FROM AUTHOR]

Linguistic register reflects changes in speech that depend on the situation, especially the status of listeners and listener-speaker relationships. Following the sociolinguistic rules of register is essential in establishing and maintaining social interactions. Recent research suggests that children over 3 years of age can understand appropriate register-listener relationships as well as the fact that people change register depending on their listeners. However, given previous findings that infants under 2 years of age have already formed both social and speech categories, it may be possible that even younger children can also understand appropriate register-listener relationships. The present study used Infant-Directed Speech (IDS) and formal Adult-Directed Speech (ADS) to examine whether 20-month-old toddlers can understand register-listener relationships. In Experiment 1, we used a violation-of-expectation method to examine whether 20-month-olds understand the individual associations between linguistic registers and listeners. Results showed that the toddlers looked significantly longer at a scene in which the adult was talked to in IDS than when the infant was talked to in IDS. In contrast, there was no difference when the adult and the infant were talked to in formal ADS. In Experiments 2 and 3, we used a habituation switch paradigm to examine whether 20-month-olds understand the abstract rule that a change of register depends on listeners rather than on speakers. Results showed that the toddlers looked significantly longer at the scene where the register rule was violated. The present findings provide new evidence that even 20-month-olds already understand that people change their way of speaking based on listeners, although their understanding of individual register-listener relationships is immature. [ABSTRACT FROM AUTHOR]

We investigate the influence of the visual appearance of a negotiator on persuasiveness within the context of negotiations. Psychological experiments were conducted to quantitatively analyze the relationship between visual appearance and the use of language. Male and female participants were shown three female and male photographs, respectively. They were asked to report how they felt about each photograph using a seven-point semantic differential (SD) scale for six affective factors (positive impression, extraversion, intelligence, conscientiousness, emotional stability, and agreeableness). Participants then answered how they felt about each negotiation scenario (they were presented with pictures and a situation combined with negotiation sentences) using a seven-point SD scale for seven affective factors (positive impression, extraversion, intelligence, conscientiousness, emotional stability, agreeableness, and degree of persuasion). Two experiments were conducted using different participant groups depending on the negotiation situations. Photographs with good or bad appearances were found to show high or low degrees of persuasion, respectively. A multiple regression equation was obtained, indicating the importance of the three language factors (euphemistic, honorific, and sympathy expressions) to impressions made during negotiation. The result shows that there are optimal negotiation sentences based on various negotiation factors, such as visual appearance and use of language. For example, persons with good appearance might worsen their impression during negotiations by using certain language, although their initial impression was positive, and persons with bad appearance could effectively improve their impressions in negotiations through their use of language, although the final impressions of their negotiation counterpart might still be more negative than those for persons with good appearance. In contrast, the impressions made by persons of normal appearance were not easily affected by their use of language. The results of the present study have significant implications for future studies of effective negotiation strategies considering visual appearance as well as gender. [ABSTRACT FROM AUTHOR]

Listeners are able to cope with between-speaker variability in speech that stems from anatomical sources (i.e. individual and sex differences in vocal tract size) and sociolinguistic sources (i.e. accents). We hypothesized that listeners adapt to these two types of variation differently because prior work indicates that adapting to speaker/sex variability may occur pre-lexically while adapting to accent variability may require learning from attention to explicit cues (i.e. feedback). In Experiment 1, we tested our hypothesis by training native Dutch listeners and Australian-English (AusE) listeners without any experience with Dutch or Flemish to discriminate between the Dutch vowels /I/ and /ε/ from a single speaker. We then tested their ability to classify /I/ and /ε/ vowels of a novel Dutch speaker (i.e. speaker or sex change only), or vowels of a novel Flemish speaker (i.e. speaker or sex change plus accent change). We found that both Dutch and AusE listeners could successfully categorize vowels if the change involved a speaker/sex change, but not if the change involved an accent change. When AusE listeners were given feedback on their categorization responses to the novel speaker in Experiment 2, they were able to successfully categorize vowels involving an accent change. These results suggest that adapting to accents may be a two-step process, whereby the first step involves adapting to speaker differences at a pre-lexical level, and the second step involves adapting to accent differences at a contextual level, where listeners have access to word meaning or are given feedback that allows them to appropriately adjust their perceptual category boundaries. [ABSTRACT FROM AUTHOR]

The classification of kin into structured groups is a diverse phenomenon which is ubiquitous in human culture. For populations which are organized into large agropastoral groupings of sedentary residence but not governed within the context of a centralised state, such as our study sample of 83 historical Bantu-speaking groups of sub-Saharan Africa, cultural kinship norms guide all aspects of everyday life and social organization. Such rules operate in part through the use of differing terminological referential systems of familial organization. Although the cross-cultural study of kinship terminology was foundational in Anthropology, few modern studies have made use of statistical advances to further our sparse understanding of the structuring and diversification of terminological systems of kinship over time. In this study we use Bayesian Markov Chain Monte Carlo methods of phylogenetic comparison to investigate the evolution of Bantu kinship terminology and reconstruct the ancestral state and diversification of cousin terminology in this family of sub-Saharan ethnolinguistic groups. Using a phylogenetic tree of Bantu languages, we then test the prominent hypothesis that structured variation in systems of cousin terminology has co-evolved alongside adaptive change in patterns of descent organization, as well as rules of residence. We find limited support for this hypothesis, and argue that the shaping of systems of kinship terminology is a multifactorial process, concluding with possible avenues of future research. [ABSTRACT FROM AUTHOR]

We perform a large-scale analysis of language diatopic variation using geotagged microblogging datasets. By collecting all Twitter messages written in Spanish over more than two years, we build a corpus from which a carefully selected list of concepts allows us to characterize Spanish varieties on a global scale. A cluster analysis proves the existence of well defined macroregions sharing common lexical properties. Remarkably enough, we find that Spanish language is split into two superdialects, namely, an urban speech used across major American and Spanish citites and a diverse form that encompasses rural areas and small towns. The latter can be further clustered into smaller varieties with a stronger regional character. [ABSTRACT FROM AUTHOR]

Human languages are rule governed, but almost invariably these rules have exceptions in the form of irregularities. Since rules in language are efficient and productive, the persistence of irregularity is an anomaly. How does irregularity linger in the face of internal (endogenous) and external (exogenous) pressures to conform to a rule? Here we address this problem by taking a detailed look at simple past tense verbs in the Corpus of Historical American English. The data show that the language is open, with many new verbs entering. At the same time, existing verbs might tend to regularize or irregularize as a consequence of internal dynamics, but overall, the amount of irregularity sustained by the language stays roughly constant over time. Despite continuous vocabulary growth, and presumably, an attendant increase in expressive power, there is no corresponding growth in irregularity. We analyze the set of irregulars, showing they may adhere to a set of minority rules, allowing for increased stability of irregularity over time. These findings contribute to the debate on how language systems become rule governed, and how and why they sustain exceptions to rules, providing insight into the interplay between the emergence and maintenance of rules and exceptions in language. [ABSTRACT FROM AUTHOR]

In the dominant theoretical framework, human communication is modeled as the faithful transmission of information. This implies that when people are involved in communicational exchanges, they should be sensitive to the success with which information is transmitted, easily detecting when conversations lack coherence. The expectation that humans are good at detecting conversational incoherence is in line with common intuition, but there are several reasons to suspect that it might be unrealistic. First, similar intuitions have been shown to be unrealistic for a number of psychological processes. Second, faithful information transmission may conflict with other conversational goals. Third, mechanisms supporting information transmission may themselves lead to cases of incoherence being missed. To ascertain the extent to which people are insensitive to patches of serious conversational incoherence, we generated such patches in the laboratory by repeatedly crossing two unrelated conversations. Across two studies, involving both narrowly and broadly focused conversations, between 27% and 42% of the conversants did not notice that their conversations had been crossed. The results of these studies suggest that it may indeed be unrealistic to model spontaneous conversation as faithful information transmission. Rather, our results are more consistent with models of communication that view it as involving noisy and error-prone inferential processes, serving multiple independent goals. [ABSTRACT FROM AUTHOR]