Interlocking Patterns of Lexis in a Corpusof Plant Biology Research Articles
Geoffrey Williams | COLEX: Centre Ouest Lexique, Faculté des Sciences, Université de Nantes
Scientific sublanguages evolve in accordance with the needs of the Discourse Community (DC) with new words being coined and a gradual change in the meanings expressed through existing lexis. In so far as the central concepts relate to each other, similar relational patterns emerge in their surface constructs, words. Consequently, the "frame of reference" for a given lexical item is to be found in the genre-specific lexical environment of that word. This is revealed through collocation, as measured using Mutual Information statistics. It is further posited that the conceptual frameworks of scientific sublanguages can be visualised through closed set collocational networks. These networks may be demonstrated locally through digraphs, but the network is posited as a more suitable means of demonstrating the complexity of relationships between individual items. The collocational networks are seen as forming the unique frame of reference for any "word" within a given sublanguage
2018. Collocation Graphs and Networks: Selected Applications. In Lexical Collocation Analysis [Quantitative Methods in the Humanities and Social Sciences, ], ► pp. 59 ff.
2019. Processing Texts in a Corpus. In Utility and Application of Language Corpora, ► pp. 73 ff.
Dash, Niladri Sekhar & L. Ramamoorthy
2019. Corpus and Technical TermBank. In Utility and Application of Language Corpora, ► pp. 173 ff.
Delfino, Maria Claudia Nunes
2021. Análise multidimensional. Cadernos de Linguística 2:4 ► pp. e474 ff.
Dubois, Vincent & Mohamed Quafafou
2002. Incremental and Dynamic Text Mining. In Foundations of Intelligent Systems [Lecture Notes in Computer Science, 2366], ► pp. 265 ff.
Dubois, Vincent & Mohamed Quafafou
2004. Graph Discovery and Visualization from Textual Data. In Intelligent Technologies for Information Analysis, ► pp. 265 ff.
Durrant, Philip
2009. Investigating the viability of a collocation list for students of English for academic purposes. English for Specific Purposes 28:3 ► pp. 157 ff.
Gablasova, Dana, Vaclav Brezina & Tony McEnery
2017. Collocations in Corpus‐Based Language Learning Research: Identifying, Comparing, and Interpreting the Evidence. Language Learning 67:S1 ► pp. 155 ff.
Gledhill, Christopher
2011. The ‘lexicogrammar’ approach to analysing phraseology and collocation in ESP texts. ASp :59 ► pp. 5 ff.
Hodges, Karen E
2008. Defining the problem: terminology and progress in ecology. Frontiers in Ecology and the Environment 6:1 ► pp. 35 ff.
Lin, Ming-Chih, Anthony J. T. Lee, Rung-Tai Kao & Kuo-Tay Chen
2011. Stock price movement prediction using representative prototypes of financial reports. ACM Transactions on Management Information Systems 2:3 ► pp. 1 ff.
Lopes, Rodrigo Esteves de Lima
2020. Reactions to Social Quotas: a study of Facebook comments in Brazilian Portuguese. Revista da ABRALIN► pp. 1 ff.
L’Homme, Marie-Claude
2019. Combinatoire spécialisée : trois perspectives et des enseignements pour la terminologie. TTR 30:1-2 ► pp. 215 ff.
Magnusson, Camilla, Antti Arppe, Tomas Eklund, Barbro Back, Hannu Vanharanta & Ari Visa
2005. The language of quarterly reports as an indicator of change in the company’s financial status. Information & Management 42:4 ► pp. 561 ff.
Magnusson, Camilla & Hannu Vanharanta
2003. Visualizing Sequences of Texts Using Collocational Networks. In Machine Learning and Data Mining in Pattern Recognition [Lecture Notes in Computer Science, 2734], ► pp. 276 ff.
Maniez, François
2002. Un modèle d’extraction des collocations en langue de spécialité. ASp :35-36 ► pp. 35 ff.
Matytcina, Marina S., Olga N. Prokhorova, Igor V. Chekulai, Vladislav A. Kuchmistyy & Oksana V. Markelova
2023. 2023 3rd International Conference on Technology Enhanced Learning in Higher Education (TELE), ► pp. 135 ff.
McEnery, Tony, Vaclav Brezina, Dana Gablasova & Jayanti Banerjee
2019. Corpus Linguistics, Learner Corpora, and SLA: Employing Technology to Analyze Language Use. Annual Review of Applied Linguistics 39 ► pp. 74 ff.
Mouri, Kousuke & Hiroaki Ogata
2015. Ubiquitous learning analytics in the real-world language learning. Smart Learning Environments 2:1
Murakami, Akira, Paul Thompson, Susan Hunston & Dominik Vajn
2017. ‘What is this corpus about?’: using topic modelling to explore a specialised corpus. Corpora 12:2 ► pp. 243 ff.
Parodi, Giovanni
2009. University genres in disciplinary domains: social sciences and humanities and basic sciences and engineering. DELTA: Documentação de Estudos em Lingüística Teórica e Aplicada 25:2 ► pp. 401 ff.
Sea-Eun Jhang, KIM ShinHo & 이성민
2015. A Comparative Analysis of Key Semantic Domains Extracted from Maritime Law English Corpus Related with Oil Spill through the Use of Wmatrix. The Jungang Journal of English Language and Literature 57:3 ► pp. 443 ff.
Sánchez-Berriel, Isabel, Octavio Santana Suárez, Virginia Gutiérrez Rodríguez & José Pérez Aguiar
2018. Network Analysis Techniques Applied to Dictionaries for Identifying Semantics in Lexical Spanish Collocations. In Lexical Collocation Analysis [Quantitative Methods in the Humanities and Social Sciences, ], ► pp. 39 ff.
2017. Implementing Sustainable Mobile Learning Initiatives for Ubiquitous Learning Log System Called SCROLL. In Mobile Learning in Higher Education in the Asia-Pacific Region [Education in the Asia-Pacific Region: Issues, Concerns and Prospects, 40], ► pp. 89 ff.
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