Relevant bibliographies by topics / Fear-including lexicon

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Academic literature on the topic 'Fear-including lexicon'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Fear-including lexicon"

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Ayupova, Lobar Murotovna. ""PRAGMALINGUISTIC ANALYSIS OF FEAR-INDUCING LEXICAL UNITS IN DETECTIVE DISCOURSE"." Journal of Universal Science Research "ZAMONAVIY TILSHUNOSLIK VA TARJIMASHUNOSLIKNING DOLZARB MUAMMOLARI" mavzusidagi xalqaro ilmiy-amaliy anjuman3 3, no. 4 (2025): 99–102. https://doi.org/10.5281/zenodo.15290510.

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This article explores the pragmalinguistic functions of fearinducing lexical units in detective discourse, comparing Uzbek (Shaytanat) and English (Sherlock Holmes) literary traditions. The study examines how linguistic tools evoke fear, analyzing semantic, syntactic, and pragmatic strategies. The findings reveal cultural and linguistic distinctions in fear representation, highlighting the role of context, metaphor, and speech acts. 
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Syafiqah, Annisa, Syahiduz Zaman, and Mochamad Imamudin. "Text Mining Approach to Emotion Analysis in Translation of Surah Yusuf With NRC Emotion Lexicon." IT Journal Research and Development 9, no. 2 (2025): 108–22. https://doi.org/10.25299/itjrd.2025.17765.

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In the digital era, the accessibility of vast textual data, including the Quran, has facilitated broader comprehension of its teachings. This study analyzes the emotions in the English translation of Surah Yusuf using the NRC Emotion Lexicon. The findings show that trust is the most dominant emotion (22.89%), followed by joy (15.66%), anticipation (13.25%), sadness (12.05%), fear (10.84%), anger (9.64%), surprise (8.43%), and disgust (7.23%). These results confirm the text's diverse emotional expressions and the effectiveness of the lexicon-based method. The research aligns with the initial go
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Horvat, Marko, Gordan Gledec, and Fran Leontić. "Hybrid Natural Language Processing Model for Sentiment Analysis during Natural Crisis." Electronics 13, no. 10 (2024): 1991. http://dx.doi.org/10.3390/electronics13101991.

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This paper introduces a novel natural language processing (NLP) model as an original approach to sentiment analysis, with a focus on understanding emotional responses during major disasters or conflicts. The model was created specifically for Croatian and is based on unigrams, but it can be used with any language that supports the n-gram model and expanded to multiple word sequences. The presented model generates a sentiment score aligned with discrete and dimensional emotion models, reliability metrics, and individual word scores using affective datasets Extended ANEW and NRC WordEmotion Asso
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Aribowo, Agus Sasmito, and Siti Khomsah. "Implementation Of Text Mining For Emotion Detection Using The Lexicon Method (Case Study: Tweets About Covid-19)." Telematika 18, no. 1 (2021): 49. http://dx.doi.org/10.31315/telematika.v18i1.4341.

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Information and news about Covid-19 received various responses from social media users, including Twitter users. Changes in netizen opinion from time to time are interesting to analyze, especially about the patterns of public sentiment and emotions contained in these opinions. Sentiment and emotional conditions can illustrate the public's response to the Covid-19 pandemic in Indonesia. This research has two objectives, first to reveal the types of public emotions that emerged during the Covid-19 pandemic in Indonesia. Second, reveal the topics or words that appear most frequently in each emoti
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HOLOTA, Taras. "Language means of manipulation in advertising on Ukrainian Telegram channels." Ukrainian Linguistics, no. 54 (2024): 177–203. https://doi.org/10.17721/um/54(2024).177-203.

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Background. With the increasing access to the internet among Ukrainians, mass media is transitioning from traditional methods of disseminating information to modern ones, such as social media channels and chatbots. This article investigates the linguistic tools of manipulation in advertisements on Ukrainian Telegram channels, focusing on “Times of Ukraine”, “Real Ukraine | Radar Alarm”, and “HK Kyiv”. Methods. The study encompasses over 950,000 word usages, including 1,200 advertising announcements, analyzed through linguistic research methods of analysis and synthesis. Results. The research i
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Öztürk, Aslı Gizem, and Metin Turan. "Sentiment Analysis Using Machine Learning Methods on News Texts." International Journal of Engineering and Computer Science 13, no. 11 (2024): 26622–40. https://doi.org/10.18535/ijecs/v13i11.4932.

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The categorization of intricate emotional phenomena in news texts permits the assessment of the impact of such news on society. In this context, it is evident that the existing body of research on emotion analysis in Turkish texts is insufficient. The objective of this study is to identify the emotions of "fear," "happiness," "anger," "sadness," and "surprise" in Turkish news texts using machine learning methods. In consideration of the Turkish language structure, the adjectives and nouns were parsed on a specially prepared corpus and dictionary groups specific to this study were created with
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Amirbekova, Aigul, Kalbike Essenova, Fariza Ismailova та ін. "Types of Сovid-Protologisms Formed in the Language Content of Kazakhstanis During the Pandemic". Theory and Practice in Language Studies 14, № 1 (2024): 51–61. http://dx.doi.org/10.17507/tpls.1401.06.

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Recently, the COVID-19 coronavirus pandemic swept the globe. As a result, the epidemiological situation and restrictive measures in the country brought significant changes to the public life of the whole world including Kazakhstan – changes that even affected the language. Indeed, COVID-19 was an impetus to the formation of new names through the internal resources of the Kazakh language, the productivity of some word-building tools, and the rapid flow of language processes. In fact, the crisis brought on by the pandemic has replenished the vocabulary of all languages of the world with new term
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Zheng, Zhi-Wei, Qing-Ling Yang, Zhong-Qi Liu, et al. "Associations Between Affective States and Sexual and Health Status Among Men Who Have Sex With Men in China: Exploratory Study Using Social Media Data." Journal of Medical Internet Research 22, no. 1 (2020): e13201. http://dx.doi.org/10.2196/13201.

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Background Affective states, including sentiment and emotion, are critical determinants of health. However, few studies among men who have sex with men (MSM) have examined sentiment and emotion specifically using real-time social media technologies. Moreover, the explorations on their associations with sexual and health status among MSM are limited. Objective This study aimed to understand and examine the associations of affective states with sexual behaviors and health status among MSM using public data from the Blued (Blued International Inc) app. Methods A total of 843,745 public postings o
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Bobrova, Maria Vladimirovna. "KOMI-PERMYAK LEXIS OF THE THEMATIC GROUP “FLORA” FROM AN ETHNOLINGUISTIC POINT OF VIEW (on the material of modern nicknames)." Yearbook of Finno-Ugric Studies 14, no. 3 (2020): 384–94. http://dx.doi.org/10.35634/2224-9443-2020-14-3-384-394.

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The article is dedicated to the lexis of the thematic group "Flora" that motivated the modern nicknames of the Komi-Permyaks living in the Perm region. Within the framework of ethnolingustics, thematic (ideographic) spheres of secondary meanings are identified in the group’s vocabulary. It is concluded that floristic lexicon is used to sign the existential, physical, psychoemotional and social characteristics of a person. Within these spheres more specific groups of cultural-semantic connotations are distinguished. The person is characterized from the following positions: 1) existance: the man
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qizi, Akhmadaliyeva Gulmira Marufjon. "The notion of fear in linguistics." International Journal Of Literature And Languages 5, no. 2 (2025): 57–59. https://doi.org/10.37547/ijll/volume05issue02-17.

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Fear is a fundamental human emotion that has been extensively studied in psychology and neuroscience. However, its impact on language and communication is equally significant. Linguistics examines how fear is expressed, shaped, and transmitted through language, revealing insights into human cognition, culture, and social structures. This article explores the linguistic dimensions of fear, including its lexical representation, metaphorical use, syntactic patterns, discourse functions, and cross-linguistic variations.
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Book chapters on the topic "Fear-including lexicon"

1

Benenowska, Iwona. "As for accepting immigrants … – an analysis of valuations and emotions in online comments (selected examples)." In E-Figurationen. Schriften zur interdisziplinären Emotionsforschung. Harrassowitz Verlag, 2025. https://doi.org/10.13173/9783447123457.109.

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The source of obtaining research material was the online forum netkobiety.pl. The main objective of the research was an attempt to determine the manner and direction of valuing immigrants in the comments on the above-mentioned forum, and to describe the synergistic emotional (and ethical) elements accompanying communicative interaction. Elements of axiolinguistic methodology were correlated with the Oldenburg concept of the “third place”, “e-expressive forms of participation” (e-women) in the (post)Habermasian ideal of inclusive (online) discursive practices. In the examples analyzed, the foll
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You might also be interested in the extended bibliographies on the topic 'Fear-including lexicon' for particular source types:
Journal articles
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