Corpus-based Approach Research Articles

A Corpus Linguistic Analysis of Characterisation in Chimamanda Ngozi Adichie’s Americanah

Research in Corpus Linguistics has provided insights into the literary meanings of texts over the past few decades. Building on this foundation, this study aims to enhance the understanding of literary texts by employing corpus tools to analyze the methods of characterisation in Chimamanda Ngozi Adichie’s novel, Americanah (2013). Specifically, it uses both quantitative and qualitative methods to examine the themes and characters in the novel, illuminating the author’s ideas and style. Through a corpus-based approach, this research examines the keywords and clusters that define the novel’s narrative structure, revealing the ideologies and literary techniques Adichie uses to craft characters and impart meaning about their experiences. The characterisation analysis uncovers recurring themes, rhetorical strategies, and linguistic patterns that enrich the portrayal of characters and narrative progression. The findings provide insights valuable for educational contexts, allowing students and readers to gain a thorough understanding of the text prior to delving into its more complex aspects.

A Corpus-based Analysis of Ten Most Frequently Used Part-of-speech Constituents in Descriptive Writing

This study is set to examine variation in the use of Part-of-Speech (POS) constituents in the contents of descriptive writing by Nigerian undergraduates using a corpus-based approach. The objective is to identify the ten most-frequently-used POS constituents they used. It also aims to identify the level of frequency variation and distribution patterns of the POS constituents used based on gender and ethnic groups. This study adopted the EAP theory and the usage-based theory. The method applied is quantitative descriptive research design and the samples include thirty (30) Nigerian undergraduates that were identified via purposive sampling. The corpus is subjected to a computer-assisted corpus analysis (CACA) where 33, 274 words were tagged and compiled. The findings revealed NN, NN1, II, AT, JJ, TO, NN2, RR and CC as the student’s ten most frequently-used POS constituents, as they achieve higher frequencies. In terms of gender variation, the findings revealed that males achieved a higher frequency of the words used, as equated with females, even though the level of variation at 0.90% is below the statistical level of significance. Also, in terms of their ethnic groups, no significant level of variation was identified, although the Igbo attained a high frequency of words-usage compared to the Yorùbá and the Hausa. Among the theoretical implications derived in this study are the deployments of the corpus-based, genre-based, EAP and ESP-oriented approaches into Nigerian ESL classroom activities.

Corpus Analysis of the Camel Concept in Kyrgyz Culture of Language

The study is devoted to a corpus analysis of the camel (төө) concept in the context of Kyrgyz culture of language. The purpose of the study is to analyze the role and meaning of the camel in Kyrgyz culture using a corpus-based approach. The study includes an analysis of the historical connection of the camel with the Kyrgyz people, its economic significance, symbolic significance in traditions and rituals, as well as a lexical and syntactic analysis of the use of the camel concept in the Kyrgyz language. The results obtained will help to better understand and interpret the role of the camel in Kyrgyz culture and its connection with the people. They will also provide valuable information about the symbolic and practical role of the camel in the daily life of the Kyrgyz people, its significance in rituals and traditions, and its representation in literature and folklore. The study will also reveal changes or adaptations in the perception and depiction of camels over time. The multifaceted role of the camel in Kyrgyz society is considered. Analysis of a variety of texts will provide a comprehensive understanding of the cultural significance of the camel in Kyrgyz society and contribute to the broader discourse on cultural heritage and identity.

Exploring network content ecosystem evaluation model based on Chinese judicial discourse of digital platform

Abstract Constructing a green and harmonious cyberspace in a network content ecosystem is a beautiful vision for millions of netizens. This study, by establishing a self-compiled corpus of judicial discourse from digital platform typical cases in China and using a combination of corpus-based approach and case analysis method, represents the development status of the Chinese network content ecosystem in order to develop a model for understanding and evaluating a network content ecosystem. Based on the analysis results of Chinese judicial discourse, an evaluation model, namely the People, Object, Technology, Organization, Government, Environment Framework (POTOGE), is derived after examining and evaluating four conceptual frameworks of the People, Process and Technology Framework (PPT), the Technology, Organization and Environment Framework (TOE), the Real Access/Real Impact Framework (RA/RI) and the People, Technology, Organization and Environment Framework (PTOE). To some extent, the POTOGE evaluation model presents a holistic and comprehensive perspective for understanding and evaluating a network content ecosystem and its key components, which can provide a reference for testing standards to ensure the sustainable development of current and future network content ecosystems. Meanwhile, the insights obtained from this study may help deepen our understanding of the judicial discourse and its thinking in the network content ecosystem. The analysis results of typical cases on digital platform can provide a reference for the formulation of future relevant laws and regulations and improve the legal protection and prevention awareness of society.

Are Textbooks Authentic From a Developmental Perspective? A Corpus Analysis of Word Use in Chinese Textbooks in US Universities

Abstract There is a prevailing belief that second language (L2) textbooks should strive for authenticity, aiming to accurately and reliably represent natural language use. However, assessing the authenticity of language textbooks is not a straightforward task, as it requires both a comparison between instructional texts and real-world language use and a consideration of the comparison within the broader context of language development. This study employs a corpus-based approach to examine word use in 31 widely used commercial textbooks across different proficiency levels, which serve as the primary resource for teaching, learning, and assessment in Chinese language programs at US universities. Using hierarchical cluster analysis, Zipf’s law analysis, and descriptive statistics, we found supportive evidence for the authenticity of word use in Chinese textbooks from a developmental perspective. Specifically, our findings reveal a nuanced gradation in the distribution of words across proficiency levels within these Chinese textbooks. Moreover, as proficiency levels increase, there is a discernible register shift in word use from spoken to written discourse. These observations carry significant implications for the utility of textbooks in Chinese language programs, particularly in the realms of instruction and assessment.

Trends in agroforestry research over 4 decades

Agroforestry has a high potential to contribute to climate change mitigation and adaptation as a nature-based climate solution and is increasingly included as a climate strategy in international agreements and national plans. Yet, how to equitably increase and sustain agroforestry on the scale needed to meet these targets remains unclear. Examining broad trends in the existing 4 decades of agroforestry literature can highlight gaps and opportunities for future research that enables agroforestry transitions. Using text analytics and a full-text, corpus-based approach, we analyzed changes in word use in 9,664 agroforestry research articles and reports published between 1980 and 2020 with regard to 4 key themes of the social dimensions of agroforestry transitions: (1) agreements and policies; (2) scales and decision-making agents; (3) knowledge, culture, and equity; and (4) frameworks and methods. We then compared the frequency of these themes in research articles and reports. Despite the most frequently used terms across all 4 decades being primarily ecological (e.g., forest, species, soil), the lexicon of agroforestry literature has expanded to incorporate more social, economic, and political elements (e.g., livelihood, knowledge, community) over time, and as agroforestry has become more central to climate change adaptation and mitigation targets. Trends in the frequency of several terms (e.g., biodiversity, development, climate) corresponded with the signing of intergovernmental agreements, illustrating the responsiveness of the field to global priorities. Reports had a higher frequency of terms related to social themes than research articles. We discuss the implications of these emergent trends and opportunities for future research in support of sustainable and just agroforestry transitions.

Telecinematic stylistics: Language and style in fantasy TV series

The language of written fantasy has been amply studied, with extensive research on authors such as JRR Tolkien, Robert E Howard, or Aldous Huxley. The study of television language, on the other hand, is attracting increasing attention, even though the scope of such research often encompasses a single TV show rather than whole genres. Given the renewed interest in all things fantasy, this study seeks to analyze the language of fantasy TV series from a corpus-stylistic perspective to open new paths for linguistic inquiry. First, I depart from a theoretical distinction that relies on Mandala’s (2012) overview of the field and James and Mendlesohn’s (2012) definitions of fantasy as a genre; I consider some of the traits they associate with written fantasy and propose a taxonomy of the different types of fantasy worlds in television. On the basis of this, I design my own TV fantasy corpus by sampling three episodes from fifteen American fantasy TV shows (2011–2021) and compare it against Davies’ TV Corpus (2021). Using a corpus-based approach, I implement a POS (part-of-speech) and semantic analysis of the corpus and consider whether, and if so how, the language of fantasy in television reflects the same characteristics scholars have identified in written fantasy and general television discourse. In doing so, I aim to contribute to the understanding of the style of fantasy as a genre and assess whether fantasy TV series are characterized by particular linguistic features.

The Russia-Ukraine conflict as a discursive continuum: A comparative study of Business Today and New York Times using an extended corpus-based discourse-historical approach

This paper presents a comparative discourse analysis of media representations of the Russia-Ukraine conflict in the American newspaper New York Times and the Indian newspaper Business Today. Using an extended corpus-based discourse-historical approach incorporating tools from critical discourse analysis and corpus linguistics, the study identifies key differences in main themes, discursive strategies, and linguistic means modulated by each nation’s geopolitics. The analysis reveals New York Times constructs the conflict predominantly as a moral and political crisis, employing critical language and ideological framing of Russia as the villain versus Ukraine as the victim. In contrast, Business Today approaches the conflict neutrally as an economic issue with pragmatic implications for India, avoiding explicit judgments and moral evaluations. While reflecting different ideological positions, the divergent framings and discursive strategies demonstrate the traditional “us versus them” dichotomy is an oversimplification. Through nuanced linguistic analysis of modal verbs, metaphors, analogies, hyperboles, and rhetorical questions, the study shows how historical relations, geopolitical interests, economic ties and cultural values create a complex discursive continuum rather than a static binary. By extending discourse-historical analysis, the paper advocates more pluralistic, self-reflexive journalism to enable nuanced policy debates attuned to on-the-ground realities, not just propagandistic binaries.

Dative possessor variation in Romance: a formal feature account with special reference to Portuguese

In this paper we address possessor dative structures (PDSs) in European Portuguese (EP) and in the Mozambican variety of Portuguese spoken in Maputo, which is mainly in contact with the Bantu language Changana. Focusing primarily on data from EP, we argue that PDSs show microvariation across Romance. We account for this microvariation by extending to Romance languages the distinction between nuclear and non-nuclear external possession structures originally proposed for Bantu languages, and propose that the value of the formal nominal feature [ipart] is the source of the observed variation. We argue that the derivation of PDSs in EP involves movement of the possessor from the specifier position of a small clause for formal feature valuation, which accounts for the common properties of give-type verbs and possessor dative structures, as well as for the incompatibility of both constructions. We further adopt a corpus-based approach and an exploratory elicitation task for the discussion of possessor datives in urban MozP. The findings support the role of the formal feature [ipart] in the acceptability of sentences which do not converge with EP, arguably as a consequence of contact with Changana, but also show that Mozambican Portuguese exhibits convergence with the VP structure of EP.

Linguocultural Specifics of Artificial Intelligence Representation in the English Language Media Discourse: Corpus-Based Approach

The article deals with the discursive construction of artificial intelligence (AI) in the English-language media discourse. Corpus methods establish semantic, figurative-perceptual and axiological specificity in the media representation of AI in various media segments, such as tabloids and broadsheet papers. Corpus-assisted discourse analysis includes: 1) identification of unique semantic domains that determine discourse interpretations of this socially significant phenomenon, followed by an analysis of their dispersion in narratives about AI; 2) analysis of the figurative-evaluative and value content of its media representation; 3) investigation of the specifics of broadsheet media and tabloid media representations of the AI concept. It was found that AI receives multiple media representations, in which its conceptual features represented by the lexical items of the semantic fields "Knowledge", "Ability", "Information and Computer Technologies" are supplemented and enriched by the lexical units of the semantic fields "Safety/Danger", "Transformation", "Ethics". In media narratives about AI, the concept of "imitation of human abilities" is often associated with fake news, plagiarism, warfare, crime, climate change, and unemployment. Corpus data revealed that in the narratives about AI in broadsheet media, the lexical items of the semantic field "Robots" emphasize the similarity of AI with anthropomorphic entities; the semantic field "Competition" represents the idea of a rivalry between a human and a machine, as well as between countries, governments and companies; the semantic field "Warfare" actualizes the pragmatics of warning related to collective security and expressing public concern about the possible negative consequences of the development of AI. Popular media emphasize the androgenic nature of AI, its entertainment potential ("Games"), practical values related to health care ("Medicines and Treatment"); and the pragmatics of warning related to individual safety ("Crime"). The evaluative media representation of AI is formed mainly by ethical and practical, often negative, evaluative features transmitted through metaphoric images, intertextual references, and cultural models that determine the behavioural patterns of the discursive community members.

Antecedents of a novel gender-neutral pronoun: a corpus-based approach to pronoun reference in Swedish

This paper provides a corpus-based perspective on the issues of pronominal systems and pronoun reference. Specifically, the paper examines the antecedents of Swedish third-person singular animate pronouns, with a particular focus on the recently introduced gender-neutral pronoun hen. Using Swedish Twitter corpora from 2015 to 2017 ( c. 1.6 billion words), the study provides a comparison of the general antecedent types as well as the specific antecedent lemmas used with each pronoun. The results show that, whilst there are considerable similarities between the use of hen and the more established gender-equal expression han eller hon (‘he or she’), hen is used substantially more often with nouns that refer to close personal relationships. In this regard, hen also bears closer resemblance to the feminine pronoun than to the masculine pronoun. Generally, the analysis demonstrates that language users are assigning a distinct set of functional properties to hen, making it a complement to the ‘old’ gender-specific and gender-equal pronouns, not a replacement.

Representations of Islam and Muslims in Media Addressed by Corpus-Based Approaches: Systematic Literature Review

In the last decade, the synergy of corpus linguistics (CL) methods within critical discourse analysis (CDA) has gained increasing popularity. This study aims to review and analyse studies related to different representations of Islam and Muslims in mainstream and alternative media addressed by corpus methodologies. It seeks to identify cross-cutting themes, similarities and differences and offer a synthesis of the literature findings to map the research topics that covered Islam and Muslims in media. Research papers are systematically searched in Web of Science, Scopus, Google Scholar, IEEE Xplore, and Science Direct from 2000 to July 2021. A total of 8 articles are selected on the basis of inclusion and exclusion criteria. All these articles are incorporated coherently to answer four predetermined research questions. This systematic literature review results show that the studies focus to a great extent only on Islam as a religion only and Muslim women, not on other topics, that are discriminatorily portrayed in the western media. In terms of women’s representations, they are depicted as either passive victims or active fighters. Whereas Islam is represented relatively negatively as an ideology, not a religion, and they use the reduction and confirmation hypothesis by selecting news articles to justify a predetermined idea. 
 Keywords: Corpus linguistics, Critical Discourse Analysis (CDA), Corpora, Islam and Muslims, newspaper discourse, media representation. Systematic Literature Review.

Developing and validating a mid-frequency word list for chemistry: a corpus-based approach using big data

Given the importance of specialized vocabulary in scientific communication and academic discourse, there is a growing need to create wordlists to address the vocabulary-learning needs of university students and researchers in different subject areas. The current study analyzed a corpus of chemistry research articles (with 278 million running words) to establish a mid-frequency vocabulary list for this field. Using frequency, range, and dispersion criteria, the study identified 560 lemmas in the fourth to the ninth British National Corpus/Corpus of Contemporary American English (BNC/COCA) lists that provided 6.4% coverage of all words in the corpus. The list was validated using specialized and general corpora, and the results confirmed the value and relevance of the items for chemistry. Moreover, for using the list for pedagogical goals, the vocabulary items were divided into five bands based on their coverage and importance. The 100 words in the first band were the most important mid-frequent vocabulary in chemistry, as they provided 3.05% coverage. The study highlights the significant contribution of mid-frequency words in research articles and the findings have implications for using large corpora as a big data source in identifying specialized and field-specific vocabulary.

An Examination of Children's Language Acquisition Through the Utilization of a Corpus-Based Approach

An Examination of Children's Language Acquisition Through the Utilization of a Corpus-Based Approach

A Corpus-based Investigation of Phrasal Complexity Features and Rhetorical Functions in Data Commentary

Introduction: In academic written texts, linguistic and rhetorical features are often interactively used as a vehicle for writers to construct their texts in order to accomplish specific communicative purposes. However, the effective integration of these resources may pose challenges for developing writers.
 Purpose: This study employed a corpus-based genre analysis approach to investigate phrasal complexity features and rhetorical functions in data commentaries written by Iranian undergraduate and graduate students. Through this approach, we aimed to examine a relatively unexplored genre of data commentary in terms of its phrasal complexity features, rhetorical functions, and their relationships. By analyzing these relationships, we sought to provide insights into the writing practices of Iranian undergraduate and graduate students in the context of data commentaries.
 Method: This study employed a convenient sampling method to select a total of 76 university students, which included 47 undergraduate students and 29 graduate students. The participants were involved in generating a corpus of 380 data commentaries, which were then thoroughly examined and compared. To identify instances of phrasal complexity features, the researchers utilized the AntConc software tool, applying regular expressions (regex) to extract potential occurrences. Additionally, a Python program was developed and implemented to calculate the frequencies of the identified PCFs. The researchers manually annotated the rhetorical function of the data commentaries to determine their specific usage.
 Results: Statistical analysis such as Mann Whitney U test and Spearman correlation test, revealed that graduate students significantly utilized more phrasal complexity features including attributive adjectives, nominalizations, and prepositional phrases (of) compared to undergraduate students. However, a qualitative analysis showed that the use of these linguistic features is influenced by the writing topics. Regarding rhetorical functions, graduate students used more moves and/or steps related to presenting and commenting data, while undergraduate students produced more moves or steps concerning personal asides. Moreover, certain phrasal complexity features and the moves and/or steps were found to be correlated, aligning with recent corpus-based studies.
 Conclusion: The study concludes with pedagogical implications.

The words that make fake stories go viral: A corpus-based approach to analyzing Russian Covid-19 disinformation

Since the outbreak of the Covid-19 pandemic in 2020, the spread of the new virus has been accompanied by the growing infodemic that became a dangerous prospect for Internet users. Social media and online messengers have been instrumental in making fake stories about Covid-19 viral. The lack of an efficient instrument for classifying digital texts as true or fake is still a big challenge. Deceptive content and its specific characteristics attract attention of many linguists, making it one of the most popular contemporary topics in corpus-based research. This paper explores the language of viral Covid-related fake stories and identifies specific linguistic features that distinguish fake stories from real (authentic) news using quantitative and qualitative approaches to text analysis. The study was conducted on the material of the self-compiled diachronic corpus containing Russian misleading coronavirus-related social media posts (a target corpus of 897 texts) which were virally shared by Russian users through social media platforms and mobile messengers from March 2020 to March 2022 and the reference corpus containing genuine materials about the virus. First, we compared two corpora using an interpretable set of features across language levels to find whether there is evidence of significant variation in the language of fake and real news. Then, we focused on frequency profiling to extract other over-represented groups of words from both corpora. Finally, we analyzed the corresponding contexts to indicate whether these features can be considered as linguistic trends in Russian Covid-related fake story making. Findings regarding the role of these over-represented groups of words in fake narratives about coronavirus revealed efficiency of frequency profiling in indicating lexical patterns of the language of deception.

Corpus-Based Approach to Sociolinguistic Study of Offensive Words: Gender, Time and Register Differences

The unpleasant expressions (offensiveness) always emotionally affect to the human psyches, and exists in all languages in less or strong degrees and directly or indirectly. Therefore, this study aimed to investigate over the changes of them by corporally-derived data and their registers, times and genders were the pilot targets. BNC and COCA Corpora were put for data collections while the list of previous insulting words was selected to reuse, especially the ones with highest frequencies. The results suggested 4 words damn, shit, fuck and dick had the highest degrees of uses but those from BNC were comparatively fewer than the rest. Moreover, the top four were emerged up to the different periods of times and contexts while men used them considerably more often than the women did.

A Corpus-Based Comparative Study of English Synonyms: Taking Improve, Promote, and Strengthen as an Example

As synonyms account for more than 60% of English vocabulary, improving the ability to distinguish synonyms will help speakers produce language in a more precise and efficient manner. This paper adopts a corpus-based approach to explore the usage of synonymous words in terms of language register, collocates and semantic prosody, exploring how these synonyms are used by native speakers and hoping to offer some guidance to English learners and translators.

A Corpus-Based Approach to Investigate the Cohesive Features Across Different Levels of CEFR

Despite plenty of previous studies pointing out the importance of validating the CEFR scale, scant attention has been given to the validation of the CEFR cohesion scale based on learners’ corpus. This study aims to examine the cohesive features of written texts at different levels of the CEFR using a corpus-based approach. Employing the TAACO and Coh-Metrix tools, this study identified identifies seven categories of key cohesive features, namely connectives, lexical overlap (sentence), Type-token ratio (TTR) and Density, givenness, semantic overlap, hypernymy and deep cohesion of the CEFR. The results showed that hypernymy and deep cohesion were the strongest predictors to distinguish CEFR levels and these categories generally kept a nonlinear relationship with CEFR levels. This study provides empirical evidence to further validate and refine the CEFR cohesion scale and casts light on the development of cohesive competence across different levels of the CEFR from the perspective of second language acquisition. More importantly, this study can provide pedagogical implications for learning and assessing cohesive competence.

SEWAR: A corpus-based N-gram approach for extracting semantically-related words from Arabic medical corpus

Automatic aggregation of similar words into semantically related groups (or clusters) is of interest to many natural language processing (NLP) applications. Extracting semantically related words and quasi-synonyms from text is a relatively new research area for the under-resourced Arabic language. Previous attempts addressed the problem of single-word term extraction. However, the absence of multiword terms (MWTs) dictionary, ontology, and semantic network makes extracting and identifying high-quality MWTs for the Arabic language a challenging problem. The main goal of this study is to extract corpus-based and coherent MWTs in the form of bigram and trigram sequences as an adequate representation of syntactic and semantic clusters. Therefore, this study contributes to this problem by implementing an algorithm named SEWAR, which uses the FastText algorithm to extract high-quality MWTs from a medical health corpus in Arabic. If put into practice, SEWAR can provide a suitable and helpful solution to classify and direct medical health questions to proper medical practitioners without human intervention. In addition, SEWAR can be applied to plenty of NLP tasks, such as information retrieval, question answering, and text summarization. Three metrics were used to assess the extracted MWTs; the pointwise mutual information (PMI), the cosine similarity, and the clustering purity measure. The results were promising and encouraging to generalize and apply SEWAR to extract MWTs from any Arabic corpus.