Collocation Networks Research Articles

U.S. administration’s press communications on Tunisia after the July 25, 2021 ‘state of exception’: The shaping of urgency discourse

July 25, 2021 was an exceptional day in Tunisia, ushering in a new chapter in its contemporary political history and triggering a wave of global responses to the declared ‘state of exception’. This research examines the U.S. administration’s press communications on Tunisia following this event. Specifically, it explores (i) the dominant crisis frames permeating these communications and their underlying political agenda and (ii) the extent to which the discourse they imparted signals a change in U.S. foreign policy towards Tunisia in crisis situations. To meet these research objectives, a corpus-based investigation was undertaken using an integrative framework combining qualitative (frames) and quantitative (keyness and collocations) approaches. Results revealed changing discourses around the theme of crisis, moving from a sense of togetherness to urgency. This may echo the cautious attitude of the American government and its heightened concern about Kais Saied’s transitional measures. In broad terms, the exploration offered a glimpse of how the dynamics of global politics unfold discursively. Importantly, the Biden administration’s construction of Tunisia’s political-democratic crisis in terms of urgency can have real-life consequences for international perceptions of the country’s future. Theoretically, the study’s implications touch primarily upon Corpus-Assisted Discourse Studies (CADS, henceforth), particularly the evolving corpus linguistics concepts of keyness and collocation networks.

Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study

This study aims at shedding light on the linguistic significance of collocation networks in the academic writing context. Following Firth’s principle “You shall know a word by the company it keeps.” The study intends to examine three selected nodes (i.e. research, study, and paper) shared collocations in an academic context. This is achieved by using the corpus linguistic tool; GraphColl in #LancsBox software version 5 which was announced in June 2020 in analyzing selected nodes. The study focuses on academic writing of two corpora which were designed and collected especially to serve the purpose of the study. The corpora consist of a collection of abstracts extracted from two different academic journals that publish for writers from different countries around the world. This corpus-based study aims at examining the significance of chunks of language in texts. The concept of collocations is crucial in corpus linguistics to identify semantic relations. This can help in the teaching and learning processes. Furthermore, this study is conducted to answer the following research questions; first, whether the three words study, paper, and research are used interchangeably in the corpora or not? Second, what are the shared collocational associations surrounding the selected nodes? Finally, it is worth noting that the study of collocations highlights the linguistic features of texts through computational analytical tools that can save time and help to gain objective results systematically. The findings show that ‘research’ and ‘study’ are used rather interchangeably in the writing of the abstracts; however, ‘paper’ has fewer shared collocations in the same academic context.

Identity construction and its collocation networks: a cross-register analysis of the finance domain

AbstractThis study investigates the use of explicit manifestations of authorial identity (namely self-mention pronouns) and their collocation networks in academic and workplace written texts. Based on a purpose-built corpus of research articles and the Hong Kong Financial Services Corpus (HKFSC), this study used Antconc and Graphcoll to extract and analyze the pronouns and their collocation networks. The statistical analysis shows that the academic register contains significantly more self-mention pronouns than the workplace corpus, which can be attributed to a stronger tendency towards self-positioning. We also identified significant register-specific semantic features of the collocation networks of self-mention pronouns. These findings contribute to our understanding of how self-mention pronouns operate in tandem with their surrounding context in register-specific discourse. Pedagogically, the findings can be useful for workshop-based training for finance students and early-career professionals in this domain to support the development of the discipline-specific writing skills needed for careers in academia and industry.

Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study

Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study

Construction of the Belt and Road Initiative in Chinese and American Media: A Critical Discourse Analysis Based on Self-Built Corpora

The Belt and Road Initiative reflects China’s ascendance in the world arena. Since its inception, this initiative has received great attention from Chinese and American media. This study applies the critical discourse analysis (CDA) method to investigate the mainstream media construction of the Belt and Road Initiative. Based on the “Lexis Advance” database, a sample of news reports dated between January, 2017 and November, 2018 were selected to build two corpora of China Daily (368 reports with 232 550 words) and The New York Times (154 reports with 106 401 words). Assisted by the two self-built corpora and the corpus software AntConc 3.2.4, the study probes into the similarities and differences between Chinese and American reports in terms of high-frequency words, collocation networks, concordance lines and concordance plots. The findings are (1) both the Chinese and American media pay great attention to the contribution of this initiative to the world economy. (2) Chinese media emphasize the concrete measures of this initiative, while American media focus on its political influence. (3) Chinese media use explicit positive vocabulary to appraise the achievement of this initiative, while American media use explicit negative vocabulary to express Trump administration’s skepticism about this initiative. (4) American government’s attitudes towards this initiative have gradually changed since Trump came to power. Though negative comments still exist, the positive voice has increased.

Analysis of the Buddhist Conversion of Great Sage

AbstractAs one of the four great classical novels of Chinese literature,The Journey to the Westnarrates a legendary Buddhist pilgrimage. Until now, the religious conversion in the novel remains much less explored by academia. We propose an innovative approach to addressing this shortfall by conducting a corpus-based investigation into the characterization of the protagonist “Great Sage.” We use the corpus tools BFSU PowerConc 1.0 and LancsBox v.2.0.1 to calculate and visualize the collocation networks of Great Sage: for one thing, to contextualize the complex interactions between him and the external environment; for another, to define and compare different phases of the character’s evolution. The collocational networks are derived by means of a quantitative approach, i.e. a mutual information (MI) score with collocation cutoff values. This lays an objective foundation for a subsequent qualitative interpretation of how the protagonist’s identity is forged in his conversion. Further, some associated literary and theological scholarships are woven into our text-based analysis.

The collocation networks of stance phrases

Collocation networks provide important information on the semantic relatedness of linguistic features and their co-texts. Previous studies on collocations have largely been limited to the descriptive examination of particular lexical items or phrases, while the statistical analysis of collocational relationships of phrases performing similar functions remains underexplored. This study investigates the collocation networks of stance phrases in cross-disciplinary academic discourse from a quantitative perspective. We used GraphColl to identify the collocates of stance phrases in two purpose-built corpora consisting of agriculture and economics research articles, and we then generated the collocation networks of different categories of stance phrases in the two corpora. The findings show a complex and intricate collocation network which displays both the within-stance category collocations and the collocational patterns between stance phrases and other semantic domains. Significant discipline-specific features were identified in the collocation networks of stance phrases. These findings contribute to our knowledge of how different categories of stance operate with their surrounding linguistic domains to assist writers to develop convincing arguments, construct coherent texts and communicate effectively with envisaged readers.

Towards Interactive Multidimensional Visualisations for Corpus Linguistics

We propose the novel application of dynamic and interactive visualisation techniques to support the iterative and exploratory investigations typical of the corpus linguistics methodology. Very large scale text analysis is already carried out in corpus-based language analysis by employing methods such as frequency profiling, keywords, concordancing, collocations and n-grams. However, at present only basic visualisation methods are utilised. In this paper, we describe case studies of multiple types of key word clouds, explorer tools for collocation networks, and compare network and language distance visualisations for online social networks. These are shown to fit better with the iterative data-driven corpus methodology, and permit some level of scalability to cope with ever increasing corpus size and complexity. In addition, they will allow corpus linguistic methods to be used more widely in the digital humanities and social sciences since the learning curve with visualisations is shallower for non-experts

Uncovering the differences in linguistic network dynamics of book and social media texts.

Complex network studies span a large variety of applications including linguistic networks. To investigate the differences in book and social media texts in terms of linguistic typology, we constructed both sequential and sentence collocation networks of book, Facebook and Twitter texts with undirected and weighted edges. The comparisons are performed using the basic parameters like average degree, modularity, average clustering coefficient, average path length, diameter, average link weight etc. We also presented the distribution graphs for node degrees, edge weights and maximum degree differences of the pairing nodes. The degree difference occurrences are furtherly detailed with the grayscale percentile plots with respect to the edge weights. We linked the network analysis with linguistic aspects like word and sentence length distributions. We concluded that linguistic typology demonstrates a formal usage in book that slightly deviates to informal in Twitter. Facebook interpolates between these media by the means of network parameters, while the informality of Twitter is mostly influenced by the character limitations.

Collocations in context

The idea that text in a particular field of discourse is organized into lexical patterns, which can be visualized as networks of words that collocate with each other, was originally proposed by Phillips (1983). This idea has important theoretical implications for our understanding of the relationship between the lexis and the text and (ultimately) between the text and the discourse community/the mind of the speaker. Although the approaches to date have offered different possibilities for constructing collocation networks, we argue that they have not yet successfully operationalized some of the desired features of such networks. In this study, we revisit the concept of collocation networks and introduce GraphColl, a new tool developed by the authors that builds collocation networks from user-defined corpora. In a case study using data from McEnery’s (2006a) study of the Society for the Reformation of Manners Corpus (SRMC), we demonstrate that collocation networks provide important insights into meaning relationships in language.