Specific Linguistic Features Research Articles

Sexisms on Facebook Page Threads of Xyriel Manabat: A Linguistic Analysis

Linguistic sensitivity is crucial in shaping individuals' thoughts, perceptions, and attitudes. The impact of language influences the creation of opportunities or the imposition of boundaries. This study delves into the realm of sexist language on the Facebook Page threads of the Filipina Child Star Xyriel Manabat, exploring both linguistic and non-linguistic aspects. Drawing on Mill's sexist language typology and Herring et al.'s framework for non-linguistic features, five posts from 2021-2022, gathering the 50 most engaging comments were analyzed. Of these, 36 comments exhibited sexist language. The findings identified five overt forms of sexism, including Naming, Insult terms, Semantic Derogation, and generic Pronouns, while indirect sexism manifested in Humor and Presupposition. Non-linguistic features, such as Emoji and Emoticons, Stickers and GIFs, Images, and Videos, were also noted in sexist comments. The conclusion drawn is that Xyriel Manabat's Facebook page comment sections contain sexist languages, characterized by specific linguistic and non-linguistic features. The study advocates for the use of gender-fair language in social media and educational settings, emphasizing the need for linguistic sexism awareness. Additionally, it encourages future research to explore other platforms and materials for comparative analysis, aiming to contribute to a broader understanding of linguistic dynamics in contemporary communication.

Analyzing Interaction Patterns on Dating Sites: A Generic Structure Potential Approach

Online dating has become a popular stage to find a romantic partner. In such context, interlocutors must employ language carefully to reveal their intentions, attract attention and as well sustain intimacy with their potential partners. While previous studies have explored aspects such as self-disclosure and linguistic strategies in impression formation, there remains a gap in understanding the structured interactions that occur between potential partners on dating sites. This study, therefore, investigated the linguistic elements and interactional structures characterizing online dating discourse, focusing on two popular platforms, Tinder and Tagged. Adopting Halliday and Hasan’s Generic Structure Potential framework, the study examined conversations of thirty participants (potential partners) whose relationship ranges between two weeks to three months. Findings revealed seven key stages: Discourse Initiation (DI), Introduction (INTR), Question and Response (QAR), Request (RQ), Admiration (AD), Declaration of Dating Intention (DDI), and Topic Formation for Conversation (TF). Each stage is marked by specific linguistic features and serves unique functions within the communication process. DI involves friendly greetings and endearments to initiate conversation and signal interest. INTR often includes declarative statements that provide personal information, establishing familiarity and a good first impression. QAR facilitates information exchange through questions and responses. RQ, predominantly by males, involves polite modal verb constructions to move the conversation to more personal platforms or obtain further information. AD includes compliments and positive affirmations to express appreciation and create a positive interaction tone. DDI features direct and indirect questions about relationship status to clarify the intent behind the interaction and define the nature of the potential relationship. Finally, TF sustains conversation with statements and questions about daily activities and interests. This study contributes to the broader understanding of professional discourse by analyzing the structured linguistic strategies and interactional patterns employed in online dating, demonstrating how individuals strategically use language to manage impressions, negotiate intentions, and build relationships – skills also crucial in professional communication.

Machine Translation and NLP Tools: Developing and Refining Language Technologies for African Languages

Machine Translation (MT) and Natural Language Processing (NLP) tools have significantly evolved over the past few decades, leading to notable advancements in the field of language technology. However, most of these developments have been concentrated on languages with abundant data, such as English, Chinese, and European languages. African languages, with their unique linguistic structures and vocabularies, remain underrepresented in the MT and NLP landscape (Joshi et al., 2020). This article explores the challenges and opportunities in creating and refining machine translation models and NLP tools tailored to the unique structures of African languages. It discusses the specific linguistic features that set African languages apart, reviews the current state of MT and NLP tools for these languages, and outlines strategies for developing more effective models that cater to the diverse linguistic landscape of Africa.

Do words matter: Investigating the association between linguistic features of accounting examinations and marks

The use of linguistic features in school assessments, as well as the impact of these factors on the outcome of assessments have received limited attention in the literature. With this study I aimed to analyse linguistic features of accounting examinations. A quantitative technique, using tests for correlation, was employed to analyse the Grade 12 National Senior Certificate accounting examinations from 2011 until 2021. Advanced textual analysis software was used to identify connections between specific linguistic features and the marks obtained in these examinations. The findings of this study suggest that increasing the levels of linguistic features associated with analytical thinking, emotional tone and big words, which may be assumed to promote comprehension, may in reality be counterproductive, consequently potentially resulting in poorer marks attained in assessments in the future. The findings of this study are important for the creators of assessment to consider when developing accounting assessment. Given the effect of linguistic features on assessment results as identified in this study, it contributes to the debate on the use of certain linguistic features in assessment.

What influences the comprehensibility of L2 writers' opinion texts by L2 readers? Interactions between textual characteristics and readers’ profiles

This study explored how L2 readers perceive the comprehensibility (i.e., ease of understanding) of L2 opinion texts in terms of reader profiles and text characteristics. We investigated how 100 Japanese learners of L2 English evaluated the comprehensibility of 16 variants of two opinion essays, which differed in lexico-grammatical accuracy, coherence, and rhetorical organization (inductive vs. deductive structure). To delve into the evaluators' backgrounds, exploratory factor analysis was conducted with a view to streamlining background variables. These variables were then compared through a t-test of two groups of readers identified by cluster analysis based on their degree of leniency or strictness. We further identified the influence of specific linguistic features on their evaluations by conducting linear mixed-effects analyses. Our findings reveal that: (1) Some L2 readers were significantly stricter than the L1 readers, whereas others were more lenient; (2) The lenient readers typically began learning English earlier, used it more extensively outside academic settings, and engaged more frequently in online communication compared to their stricter counterparts; and (3) Though disrupted sequences of ideas (coherence errors) were universally detrimental to comprehensibility, lexico-grammatical errors significantly impacted only the strict readers, not the lenient ones.

Exploiting ChatGPT for Diagnosing Autism-Associated Language Disorders and Identifying Distinct Features.

Diagnosing language disorders associated with autism is a complex and nuanced challenge, often hindered by the subjective nature and variability of traditional assessment methods. Traditional diagnostic methods not only require intensive human effort but also often result in delayed interventions due to their lack of speed and specificity. In this study, we explored the application of ChatGPT, a state-of-the-art large language model, to overcome these obstacles by enhancing diagnostic accuracy and profiling specific linguistic features indicative of autism. Leveraging ChatGPT's advanced natural language processing capabilities, this research aims to streamline and refine the diagnostic process. Specifically, we compared ChatGPT's performance with that of conventional supervised learning models, including BERT, a model acclaimed for its effectiveness in various natural language processing tasks. We showed that ChatGPT substantially outperformed these models, achieving over 13% improvement in both accuracy and F1-score in a zero-shot learning configuration. This marked enhancement highlights the model's potential as a superior tool for neurological diagnostics. Additionally, we identified ten distinct features of autism-associated language disorders that vary significantly across different experimental scenarios. These features, which included echolalia, pronoun reversal, and atypical language usage, were crucial for accurately diagnosing ASD and customizing treatment plans. Together, our findings advocate for adopting sophisticated AI tools like ChatGPT in clinical settings to assess and diagnose developmental disorders. Our approach not only promises greater diagnostic precision but also aligns with the goals of personalized medicine, potentially transforming the evaluation landscape for autism and similar neurological conditions.

Analyzing the impact of unemployment on mental health among Chinese university graduates: a study of emotional and linguistic patterns on Weibo.

This study explores the intricate relationship between unemployment rates and emotional responses among Chinese university graduates, analyzing how these factors correlate with specific linguistic features on the popular social media platform Sina Weibo. The goal is to uncover patterns that elucidate the psychological and emotional dimensions of unemployment challenges among this demographic. The analysis utilized a dataset of 30,540 Sina Weibo posts containing specific keywords related to unemployment and anxiety, collected from January 2019 to June 2023. The posts were pre-processed to eliminate noise and refine the data quality. Linear regression and textual analyses were employed to identify correlations between unemployment rates for individuals aged 16-24 and the linguistic characteristics of the posts. The study found significant fluctuations in urban youth unemployment rates, peaking at 21.3% in June 2023. A corresponding increase in anxiety-related expressions was noted in the social media posts, with peak expressions aligning with high unemployment rates. Linguistic analysis revealed that the category of "Affect" showed a strong positive correlation with unemployment rates, indicating increased emotional expression alongside rising unemployment. Other categories such as "Negative emotion" and "Sadness" also showed significant correlations, highlighting a robust relationship between economic challenges and emotional distress. The findings underscore the profound impact of unemployment on the emotional well-being of university students, suggesting that economic hardships are closely linked to psychological stress and heightened negative emotions. This study contributes to a holistic understanding of the socio-economic challenges faced by young adults, advocating for comprehensive support systems that address both the economic and psychological facets of unemployment.

Linguistic correlates of societal variation: A quantitative analysis.

Traditionally, many researchers have supported a uniformitarian view whereby all languages are of roughly equal complexity, facilitated by internal trade-offs between complexity at different levels, such as morphology and syntax. The extent to which the speakers' societies influence the trade-offs has not been well studied. In this paper, we focus on morphology and syntax, and report significant correlations between specific linguistic and societal features, in particular those relating to exoteric (open) vs. esoteric (close-knit) society types, characterizable in terms of population size, mobility, communication across distances, etc. We conduct an exhaustive quantitative analysis drawing upon WALS, D-Place, Ethnologue and Glottolog, finding some support for our hypothesis that languages spoken by exoteric societies tend towards more complex syntaxes, while languages spoken by esoteric societies tend towards more complex morphologies.

Dementia stigma: representation and language use

Linguistic choices are widely understood to have the potential to contribute to, but also to challenge, dementia stigma. This scoping review therefore aims to better understand: 1) the characteristics of language-oriented studies into representations of dementia and people with dementia, particularly regarding theoretical engagement with dementia stigma; and 2) what specific linguistic features have the potential to contribute to and/or challenge dementia stigma. Using Scopus, PubMed, PsychInfo and Google Scholar, 44 papers published between January 2000 and December 2022 were selected and thematically synthesized. We found that the number of publications addressing language and dementia stigma increased dramatically over the period covered. Most studies (75 %) did not explicitly define their use of the term stigma, and those that did drew on a range of theories and sources. Linguistic features associated with stigma included catastrophizing metaphors and the personification of dementia as a cruel enemy. Distancing and delegitimizing strategies were popularly used for people living with dementia, including homogenization, negative group labels, dehumanizing metaphors, infantilization and passivization. Humor could be used to perpetuate dementia stigma, but also to resist and reclaim stigmatizing discourses. Dementia stigma could be challenged through redefining the roles attributed to social actors, directly critiquing harmful discourses, and by providing counter-discourses. Counter-discourses used normalizing, holistic, person-centerd, rights-based, optimistic and affirmative language. Overall, a complex picture of language and dementia stigma emerges. Based on our review of the 44 papers considered, we argue that much language has the potential to perpetuate or resist stigma, and that this is shaped by and depends upon the broader discursive context within which such language use takes place.

Image of Vlad III Basarab in German Sources of the 15th-16th Centuries

The article is devoted to the problem of the emergence of German texts about Dracula in Germany in the 15th-16th centuries and their genre evolution associated with a change in the linguo-pragmatic task. The links between the works about Dracula belonging to different genres are considered: the handwritten pamphlet of the Benedictine monks from Lambach, the historical episode in the “Chronicle of Constance” by Gebhard Daher, the poetic arrangement of “About the villain called Dracula the Voda of Wallachia” by the court poet Michael Beheim, an entertaining story in early printed editions – “folk books”. The article shows how, depending on the historical situation, the evaluative position and goals of the compilers of the texts changed, and what effect this had on specific linguistic features, primarily lexical ones. he works of Antonio Bonfini and Teodor Kuritan do not seem to have influenced the German Dracula narratives: even the later German texts are close in content to the Lambach manuscripts.

Techniques of speech influence in the final part of the promotional video for online courses

Due to the growing number of online courses, authors have to use more and more speech impact techniques in promotional videos to attract listeners and induce them to take action. Advertising video, being an independent speech genre, having a stable composition and certain content, as well as a set of specific linguistic features, requires special study. The aim of the study is to identify the optimal linguistic techniques of RW in the final part of the promotional video for online courses accompanying linguistic educational resources. 117 promotional videos for Massive Open Online Courses in Russian language posted on the open platform were used for the analysis. The main methods and techniques used are: the method of scientific description and stylistic and contextual analysis. The techniques used in the final part of the speech were singled out, their quantitative analysis was carried out: 1) invitation of the listener to the course, 2) appeal to the goal of the listener or the goal of the online course, 3) appeal to quotations, 4) generalizing conclusion, 5) humorous ending, 6) advice for listeners, 7) containing a call to action, 8) farewell. The scientific novelty of the study lies in the fact that 1) for the first time the promotional video for online courses is considered as a complex communicative discourse, i.e. the synthesis of advertising and educational discourse; 2) for the first time the methods of speech impact in promotional videos for online courses are studied. Promotional videos for online courses presented on the platform "Education in Russian" contain a certain set of RW techniques, mainly used in the final part of the video and characterized by a specific set of linguistic means (mainly verbs) that can be embodied in the speech genres of "Advice" and "Wishes".

Use Of Spoken Corpora in Language Learning and Teaching

This article discusses the use of spoken corpora to enhance language learners' listening comprehension skills. Spoken corpora provide learners with exposure to authentic spoken language, allowing them to familiarize themselves with natural speech patterns, intonation, and colloquial expressions. Learners can engage in various activities such as transcription, note-taking, and comparative listening to develop their listening accuracy and ability to recognize spoken words and structures. Online platforms and resources like TED Talks, YouTube channels, and linguistic archives such as the International Dialects of English Archive offer valuable spoken corpora for language learners. These resources provide opportunities for listening practice, interactive activities, and targeted learning of specific linguistic features.

On-Air, Off-Balance: Detecting and Examining Media Biases in Filipino Sportscasting

With sports gaining global acclaim and recognition, media outlets have extensively covered a myriad of sporting events with a particular emphasis on international tournaments. In the digital age, media is crucial for disseminating news and shaping audience perspectives especially in sportscasting where local sportscasters tend to show affection and allegiance to their home nation by providing more airtime and positive commentaries to athletes representing their country. Such an approach shortchanges the viewers’ right to unbiased and diverse perspectives. Hence, it is imperative for media outlets, particularly during live sports broadcasts, to adeptly navigate and manage biases, given the significant impact of nationalistic positioning on sports media. In this study, the researchers analyzed the language employed by sportscasters in the local media coverage of the games of the Philippines Men’s Basketball Team, also known as Gilas Pilipinas, during the FIBA World Cup 2023. Following a mixed-method approach, the study sought to understand how sportscasters detect and manage media biases through corpus analysis. The investigation involved identifying prevalent forms of media biases within the study corpus, focusing on lexico-semantic, discourse, and pragmatic constructions that serve as indicators of these biases. The study findings indicated that all the analyzed sports broadcasts contained evident manifestations of media biases. Moreover, it was revealed that Filipino sportscasters exhibited a range of media biases favoring Gilas Pilipinas, and that the media biases in their utterances were affected by the phenomenon of nationalistic positioning that raises concerns about fairness and impartiality. Consequently, the frequency of these biased expressions in sportscasters' utterances was found to be contingent upon the specific context, varying with the situation. Furthermore, these biases can be identified through specific linguistic cues and features. This paper underscores the importance of fostering a more equitable sportscasting environment while simultaneously fortifying language and media education initiatives.

The adaptive community-response (ACR) method for collecting misinformation on social media

Social media can be a major accelerator of the spread of misinformation, thereby potentially compromising both individual well-being and social cohesion. Despite significant recent advances, the study of online misinformation is a relatively young field facing several (methodological) challenges. In this regard, the detection of online misinformation has proven difficult, as online large-scale data streams require (semi-)automated, highly specific and therefore sophisticated methods to separate posts containing misinformation from irrelevant posts. In the present paper, we introduce the adaptive community-response (ACR) method, an unsupervised technique for the large-scale collection of misinformation on Twitter (now known as ’X’). The ACR method is based on previous findings showing that Twitter users occasionally reply to misinformation with fact-checking by referring to specific fact-checking sites (crowdsourced fact-checking). In a first step, we captured such misinforming but fact-checked tweets. These tweets were used in a second step to extract specific linguistic features (keywords), enabling us to collect also those misinforming tweets that were not fact-checked at all as a third step. We initially present a mathematical framework of our method, followed by an explicit algorithmic implementation. We then evaluate ACR on the basis of a comprehensive dataset consisting of >25\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$>25$$\\end{document} million tweets, belonging to >300\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$>300$$\\end{document} misinforming stories. Our evaluation shows that ACR is a useful extension to the methods pool of the field, enabling researchers to collect online misinformation more comprehensively. Text similarity measures clearly indicated correspondence between the claims of false stories and the ACR tweets, even though ACR performance was heterogeneously distributed across the stories. A baseline comparison to the fact-checked tweets showed that the ACR method can detect story-related tweets to a comparable degree, while being sensitive to different types of tweets: Fact-checked tweets tend to be driven by high outreach (as indicated by a high number of retweets), whereas the sensitivity of the ACR method extends to tweets exhibiting lower outreach. Taken together, ACR’s capacity as a valuable methodological contribution to the field is based on (i) the adoption of prior, pioneering research in the field, (ii) a well-formalized mathematical framework and (iii) an empirical foundation via a comprehensive set of indicators.

Some bilingual couples speak lingua francas: personal pronoun indexicality in the light of positioning theory

ABSTRACT The paper focuses on the communication of three bilingual couples, each speaking a different lingua franca (LF). Positioning theory offers a methodological framework to explain language choice in interactive positioning within personal contacts. A comparative view of the couples’ storylines benefits from the differences between them. The analysis herein shows how the speakers are positioned in the subtle interplay of self-positioning and the positioning of the partner. The couples draw on their language resources and specific linguistic features which index language ideologies. Reasons for the choice and maintenance of a LF in the couple are informed by attitudinal factors which contribute to the discursive production of interpersonal positions. Findings outline multidimensional perspectives on LF couples by showing how different positions are created and how positioning is connected to the negotiation of a common language. This paper advances the debate on LF communication in intercultural relationships by demonstrating that positioning helps to investigate the ways in which diverse language resources intertwine to create different linguistic constellations and eventually improve our understanding of the performance in a third language.

Translation of Metaphorical Information in Japanese Literature Combined with Text Mining Techniques

Abstract Japanese literature is renowned for its conciseness and the profound, multi-layered meanings conveyed through its economical use of language and rich symbolic content. This paper explores the creative impact of these linguistic features in Japanese literature by analyzing the deep meanings and varied classifications of literary metaphors. The construction of a Japanese literature corpus involved the collection, cleaning, and organization of Japanese literary texts, followed by the selection of specific linguistic features. The corpus was then aligned using a dynamic programming approximation algorithm. A semantic representation model of the Japanese literature text corpus was developed by integrating the Attention Word Embedding Model with the Extended Topic Information Model, and metaphoric corpus features were fused using the static fusion strategy of Extended Topic Information and Attention Word Embedding. This study also examines the translation of symbolic information in Japanese literature, focusing on linguistic and stylistic features. The findings reveal that translations into Chinese tend to employ augmentation translation, resulting in 1,706 additional sentences compared to the original Japanese texts. Furthermore, the lexical density in the Chinese translation reference corpus is 2.45 percentage points higher than in the Japanese literature corpus. Analysis of verb modifications shows that among the 90 altered verbs in the Chinese translation corpus, only 24 have corresponding instances in the original Japanese texts. Text mining techniques were employed to conduct a deep analysis of symbolic content, enhancing the understanding of the nuanced connotations inherent in Japanese literature.

FEATURES OF THE CONCEPT “HEALTH/UNHEALTH” AND ITS SPECIFICITY OF REPRODUCTION IN MODERN ENGLISH SERIES

The article focuses on the study of the lexical-semantic and genre-stylistic aspects of the concept "HEALTH/ILLNESS" and the specifics of reproduction in modern English-language TV series.. Analyzing the concept "HEALTH/ILLNESS" in the lexical-semantic aspect according to dictionary definitions, it was established that they do not always have a clear definition, as they can be perceived subjectively and determined by cultural and social contexts. Although there are generally accepted standards, the interpretation of symptoms and assessment of health status may vary among different professionals and individuals. Considering different views on the concept of "HEALTH/ILLNESS" we can consider the main approaches to its definition — traditional medical concept, the World Health Organization (WHO) concept, and the ecological concept. The concept "HEALTH/ILLNESS" in medical texts has its own specific stylistic and linguistic features. This includes the use of specialized terminology, nominalization of verbs and adjectives, medical jargon, extended nominative groups/phrases, causal verbs, impersonal language and the use of internationalisms. The public's understanding of the concept "HEALTH/ILLNESS" is largely formed through various sources of information, in particular through English-language TV series. Contemporary TV series have been found to have a major impact on public perception and awareness of the importance of research and treatment for various diseases, including neurodegenerative diseases. Since the concept of "health/illness" is considered from different points of view, several micro-concepts were distinguished using frame analysis, namely: physical health, mental health, medical therapy and recovery, diagnostic process, modern approaches to treatment, health insurance systems, and ensuring access to medical care.

Grice's Maxims in Moroccan EFL: A Cultural Approach through Optimality Theory

The primary objective of the present study is to examine the structure of Grice's Maxims within the particular cultural setting of Morocco. The aim of this investigation is to scrutinize the impact of societal expectations and linguistic strategies on the production of conversational implicatures in the Moroccan cultural context. The present investigation employs Optimality Theory as a theoretical framework to examine a range of factors, such as power dynamics, social distance, politeness, sarcasm, and specific linguistic characteristics within the social and cultural context of Moroccan Arabic. This study argues that an understanding of the appropriate use of conversational implicatures enhances the cross-cultural competence of English as a Foreign Language (EFL) Moroccan Learners. The findings reveal the complexity of various constraints that shape the process of Moroccan conversational decision-making, unveiling noteworthy differences in comparison to the norms common to Western culture. The employment of the participant observation technique enabled a thorough investigation that was authentic and culturally sensitive, thereby enriching the understanding of conversational implicatures in a diverse global setting.

Too influential to be overlooked: How a Social Practice View of Health Literacy and Health Promotion is Transforming Research and Intervention

Abstract Introduction The history of public health shows that our conceptualization of a study object (e.g. sustainability) influences how researchers perceive, explore, assess, and derive insights from it. Thus, a sound conceptualization is essential. Much debate has raged about the proper conceptualization of health literacy (HL). With the increasing focus on HL intervention research, a conceptualization grounded in practice is irreplaceable and needs to be reflected theoretically. This presentation will discuss the conceptualization of HL as situational social practice and the implications for HL research and interventions, based on ethnographic data of an educational settings, language courses. These courses are well suited to explore practices around HL, as their purpose is not to impart information but to promote competences and communicative skills in the life domain of health. Methods Ethnographic research including textbook analysis and participant observation in two second language courses in Germany (100 hours) explored the role, manifestation, and promotion of health and HL. Then practice-oriented evidence-informed interventions were developed and general insights derived. Results We identified more than 500 events for engaging with health information, utterly rich and complex and characterized by specific linguistic, situational, social, practice-related, and contextual features. Despite the same cultural portrayal and contextual influences, the learners’ and teachers’ practices proved to be diverse, varied from imitating to changing to creating. We developed complex interventions that provided teachers with both a social-practice-view on HL, the skills to purposefully promote it, and materials. Discussion Any use of HL is a situational social practice, and consciously taking this perspective allows us to better understand, explore the spaces and constraints for action, and develop more targeted interventions towards sustainability.

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.