Search

Using Internet search data may reveal intentions and expectations in various areas of scientific interest in social sciences. One of them is media studies and especially the research of media literacy, where search engines such as Google can shape the way of investigation of current social trends and academic discourse in the field. In this paper, we analyse various ways of using specific data gathered by Google and delivered by the Google Trends service. We examine whether the online activity measured by Google searches can be a valid source of information to investigate how social trends correlate with current media literacy topics and areas of scientific interest. This paper provides some examples of how researchers could use Google Trends service to study specific search terms such as 'fake news', 'hoaxes' and other emerging collocations with which media literacy research is concerned. We conducted time series on Google search data to investigate the continuity of these terms with current geopolitical events, as well as significant social and political events, such as the election of the US president. We discuss ways in which we can use these emerging sources of data to investigate how social trends evolve over time. [ABSTRACT FROM AUTHOR]

Quantitative methods applied to corpus data allow researchers to evaluate the represented results. Statistical association measures are used to evaluate the collocation strength and to produce lists of most plausible collocations. Such information about words' collocability supplied with statistical data can be used in many areas of computational and applied linguistics. The paper deals with the description of an integrated Russian collocations database that will contain automatically extracted collocations evaluated against dictionaries and linguistic expertise. Despite the fact there are collocations dictionaries for Russian there is still a need in a comprehensive collocation description. The aim of the tool is to provide information about collocational preferences of frequent lexemes supplied with additional information and examples from general and specialized corpora and other resources. The present tool can be used in natural language processing for parse filtering, word sense disambiguation, in lexicography, machine translation and language learning. [ABSTRACT FROM AUTHOR]

Collocation extraction is a prominent task in natural language processing, its results are important in various areas of applied linguistics. The research focuses on a comparison between seven statistical measures based on the large Russian ruTenTen corpus. The paper examines the bigrams with a number of Russian high-frequency nouns that were extracted by the given measures. The analysis is organized in two ways. First, we ranked the lists of bigrams obtained by each measure and evaluated the results against the Russian dictionaries identifying automatically extracted and manually collected collocations. The second experiment involved the comparison between each pair of measures in order to determine to what extent they produce the same results. The results show that dictionary collocations have higher rankings in the lists. Also the produced bigrams can be considered as collocations by experts and thus may enrich dictionaries. Several measures prove to demonstrate a relative interchangeability giving the overlapping results. [ABSTRACT FROM AUTHOR]

The article is aimed on the research of individual style of Vladimir Nabokov writing through the analysis of colour collocations with component “grey” functioning in the novel Lolita and in the author’s translation of it into Russian. The problem is reviewed by the researchers from the positions of Combinatorial Linguistics and Semantics of Colour. The methodological base of the study is “Harmonious Translation space” conception developed by Prof. L.V. Kushnina (Russia, Perm). As for the result we can assume that in Lolita and its translation Nabokov used different collocations to define colour. Analyzing them we can better understand his individual style and what was the most important to him as the author and translator. For example, in Russian translation the colour pallette is much wider and there are allusions that only language speaker can understand. Nabokov didn't translate one word the same way throughout the book. He also could explain some things which he thought didn't exist in the reader's worldview. [ABSTRACT FROM AUTHOR]

The study is focused on the process of searching bilingual terminology on the Web in the translation process. The experimental data were gathered using computer monitoring (keylogging) and post-translation interviewing. A group of translators was given a short text containing educational terminology with multiple equivalents in the target language. The task was to translate the text with a focus on terminology equivalence and consistency. The computer monitoring data include keyboard activity, a list of Web resources consulted, screenshots, and video recordings of the screen. Logging data were presented as step-by-step sequences of actions in the course of searching for particular equivalents. During the post-translation interviewing, the testees gave comments on taking particular steps in terminology searching, periods of zero activity, and decision making. The results show that in searching for terminology translators perform several key types of activities: searching for potential equivalents, searching for definitions or explanatory contexts (both source and target terminology), verifying potential equivalents, and searching particular collocations with target terminology. A particular sequence rarely includes all types of activities and may represent an iterative process of performing similar activities. The quality of translation does not relate to the number of activities; however, there is a certain correlation between the quality and types of activities performed. [ABSTRACT FROM AUTHOR]