Lexical Richness of Abstracts in Scientific Papers in Anglophone and Non-Anglophone Journals

Abstract

Journal research article abstracts, considered as the most read section of the entire paper, have been the focus of multi-dimensional research studies. In the genre of abstracts, vocabulary richness is the basis for the construction of sentences, paragraphs, and complete texts; it contributes to non-native (and even native) English speakers of the language in the production and comprehension of written texts. To explore its importance, the present study examines the lexical richness in abstracts of scientific papers; it consists of three distinct measurement dimensions: lexical density, lexical variation, and lexical sophistication. The comparative-descriptive analysis is based on a corpus of abstracts in English published in Anglophone and non-Anglophone contexts. The written corpora were subjected to a software-driven text analysis using the complete lextutor vocab-profile available online at https://www.lextutor.ca/vp/eng/; the output texts from the software analyser were mined using SPSS statistics. Results show that although abstracts in both publication contexts use varied and extensive vocabulary throughout the two English sub-corpora, Anglophone texts, unlike non-Anglophone ones, produce more content and off-list words. This study announces valuable insights, particularly for inexperienced and novice writers, on using automatic online tools, such as vocab-profile, to gauge the type of vocabulary used in their written compositions.

Exploring corpus linguistics via computational tool analysis: key finding review

“…These tools can discern patterns and meanings in a manner like that of human comprehension [30]. Among the most notable NLP tools are Wordify [8], Mlphon [31], morphological analyzer [32], Runyakitara tool [33], LexTutor [34], [35], Coh-Metric [36], [37] linguistic queries and word count (LIWC) [38], UAM corpus tool [39], [40], SketchEngine (SkE) [41], Wmatrix [37] MultiAzterTest [42], sublanguage corpus analysis toolkit (SubCAT) [43], EnvText [44], InLang [45], Berri corpus manager [46], UCREL semantic analysis system (USAS) [47], PyMongo (Mongo DB, Python technology, Flask) [46], LancsBox 5.1.2 [48], LancsBox 4.5 [49], LancsBox [50], NooJ platform [51] and Bi-LSTM [52].…”

“…There are various benefits of all the corpus tool that have been expressed and benefited researchers, and this tool has supported their study data from various aspects e.g. in terms of linguistic competence and features [42], language functioning and patterns [33], digital corpora [56], lexical richness [35], flexible database, multidimensional measures of language quality [37], and multilingual analysis [50]. Accessibility and open data initiatives are promoted to make diverse corpora more accessible to researchers.…”

The Compleat Lextutor Application Tool for Academic and Technological Lexical Learning: Review and Bibliometric Approach

“…For example, Abduh and Rosmaladewi (2017) investigated the use of CLA for assessing university students' vocabulary levels majoring in Business English at a public Indonesian university. Viera (2022) researched lexical diversity by comparing abstracts from published manuscripts written in English-speaking countries and non-English-speaking nations. Further, Wiranty (2022) portrayed the vocabulary profile that is used in the reading passage of the national entrance tests of Indonesian public universities.…”