The semantic field of comicality in clickbait headlines
DOI:
https://doi.org/10.47475/2070-0695-2022-10110Keywords:
clickbait, comicality, media text, semanticsAbstract
The article is devoted to the analysis of clickbait headlines in terms of the semantics of comicality. The purpose of the article is to classify clickbaits and to show how they work. As the main source of the empirical base, one of the largest Russian news portals, Lenta.ru, was used. The study uses modeling technique for the deductive pragmalinguistic interpretation of clickbait headlines. As a result, the clickbait model using comicality appears in the following components: 1) a stimulating remark of the clickbait subject, containing a promise; 2) verbal and non-verbal markers of the object of laughter; 3) markers of the supposed laughter response to a stimulus.
References
Ageeva, G. A. & Smyshlyaeva, V. A. (2019). Clickbait: etimologiya, semantika, sredstva vyrazheniya [Clickbait: etymology, semantics, means of expression]. Molodezhnyy vestnik IrGTU [Young Researchers Journal of ISTU], 9(1), pp. 153–158. (in Russ.).
Antologiya rechevykh zhanrov: povsednevnaya kommunikatsiya [Anthology of Speech Genres: Everyday Communication]. (2007). Moscow: Labirint, 320 p. (in Russ.).
Bakhtin, M. M. (1996). Sobranie sochineniy v 7 tomakh. T. 5 [Collected works in 7 volumes. Vol. 5]. Problema rechevykh zhanrov [The problem of speech genres]. Moscow: Russkie slovari, pp. 159–206. (in Russ.).
Vezhbitska, A. (1997). Rechevye zhanry [Speech genres]. Zhanry rechi [Genres of speech], Saratov: Kolledzh, 1, pp. 23–33. (in Russ.).
Vinokur, T. G. (1993). Govoryashchiy i slushayushchiy: Varianty rechevogo povedeniya [Speaking and Listening: Variants of Speech Behavior]. Moscow: Nauka, 172 p. (in Russ.).
Vol'skaya, N. N. (2018). Klikbeyt kak sredstvo sozdaniya lozhnoy informatsii v internet-kommunikatsii [Clickbait as a means of creating false information in Internet communication]. Mediaskop [Mediascope], available at: http://www.mediascope.ru/2450 (accessed 12.09.2021). DOI: 10.30547/mediascope.2.2018.12. (in Russ.).
Gavrikova, O. A. (2018). Kriterii vyyavleniya klikbeyt-zagolovkov [Criteria for identifying clickbait headlines]. Yazykovye edinitsy v svete sovremennykh nauchnykh paradigm. Materialy IV Vserossiyskoy nauchno-prakticheskoy konferentsii s mezhdunarodnym uchastiem, Ufa, 20 dekabrya 2018 g. [Language units in the light of modern scientific paradigms. Materials of the IV All-Russian scientific-practical conference with international participation, Ufa, 20 December 2018]. Ufa, pp. 23–28. (in Russ.).
Gavrikova, O. A. (2018). O fastsinativnom vospriyatii klikbeyt-form v interdiskursivnom prostranstve [On fascinative perception of clickbait forms in interdiscursive space]. Doklady Bashkirskogo universiteta [Proceedings of Bashkir University], 3(1), pp. 94–99. (in Russ.).
Gavrikova, O. A. (2018). Smyslovoe iskazhenie informatsii v klikbeyt-zagolovkakh v tekstakh politicheskogo mediadiskursa [Semantic distortion of information in clickbait headings in texts of political media discourse]. Vestnik Bashkirskogo universiteta [Bulletin of Bashkir University], 23(1), pp. 173–178. DOI: 10.33184/bulletin-bsu-2018.1.28. (in Russ.).
Dement'ev, V. V. (2006). Nepryamaya kommunikatsiya [Indirect communication]. Moscow: Gnozis, 376 p. (in Russ.).
Dement'ev, V. V. (2010). Teoriya rechevykh zhanrov [Theory of speech genres]. Moscow: Znak, 600 p. (in Russ.).
Klyuev, E. V. (2004). Faticheskaya funktsiya yazyka i problemy referentsii [Phatic function of language and problems of reference], available at: http://www.kluev.com/?p=5. (in Russ.).
Kornilova, N. A. (2013). Faticheskaya rech' v massmedia: kompozitsionno-stilisticheskie formy [Phatic speech in mass media: compositional and stylistic forms]. Candidate of sciences thesis. Saint Peterburg. (in Russ.).
Nikolaeva, A. V. (2017). Klikbeyt: k opredeleniyu ponyatiya [Clickbait: to the definition of the concept]. Aktual'nye problemy stilistiki [Actual problems of style], 3, pp. 146–151. (in Russ.).
Prokof'eva, N. A. (2016). Anons. Rechezhanrovaya forma kontaktoustanovleniya v mediadiskurse [Announcement. Speech and Genre Form of Contact Establishment in Media Discourse]. Slavyanskiy mir i natsional'naya rechevaya kul'tura v sovremennoy kommunikatsii. K 155-letiyu so dnya rozhdeniya akademika Evfimiya Fedorovicha Karskogo; gl. red. M. I. Konyushkevich; red. kol.: M. I. Konyushkevich, T. A. Pivovarchik & I. I. Minchuk [Slavic world and national speech culture in modern communication. By the 155th anniversary of the Birthday of Academician Eviefmy Fedorovich Karsky; main editor M. I. Konyushkevich; editors: M. I. Konyushkevich, T. A. Pivovarchik & I. I. Minchuk]. Grodno: GrGU im. Yanki Kupaly, pp. 274–283. (in Russ.).
Solov'ev, A. (2018). Klikbeyt-zagolovki v reklame: ispol'zovat' nel'zya ignorirovat' [Clickbait Headlines in Ads]. Zhurnalіstyka-2018: stan, prablemy і perspektyvy: materyyaly 20-y Mіzhnar. navuk.-prakt. kanf. Mіnsk, 15-16 lіst. 2018 g. [Journalism 2018: state, problems and prospects: materials of the 20th International. scientific-practical conf. Minsk, 15-16 November 2018]. Pp. 253–255. (in Russ.).
Surikova, T. (2019). Konstanty yazyka sovremennykh massmedia kak istochnik lingvoeticheskikh kolliziy [Constants of the Language of Modern Mass Media as a Source of Linguistic and Ethical Collisions]. Slova ў kantekstse chasu. Materyyaly IV Mіzhnarodnay navukova-praktychnay kanferentsyі, prysvechanay 90-goddzyu z dnya naradzhennya doktara fіlalagіchnykh navuk prafesara A.І. Narkevіcha. Mіnsk, 14-15 marta 2019 g. [The word in the context of time. Proceedings of the IV International Scientific and Practical Conference dedicated to the 90th anniversary of the birth of Doctor of Philology, Professor A.I. Narkevich. Minsk, 14-15 March 2019]. Pp. 110–112. (in Russ.).
Chanysheva, Z. Z. (2016). Informatsionnye tekhnologii smyslovykh iskazheniy v klikbeyt-zagolovkakh [Information technology of semantic distortions in clickbait headings]. Vestnik Permskogo natsional'nogo issledovatel'skogo politekhnicheskogo universiteta. Problemy yazykoznaniya i pedagogiki [PNRPU Linguistics and Pedagogy Bulletin], 4, pp. 54–62. DOI: 0.15593/2224-9389/2016.4.5. (in Russ.).
Chepkina, E. V. (2000). Russkiy zhurnalistskiy diskurs: Tekstoporozhdayushchie praktiki i kody [Russian journalistic discourse: Text-generating practices and codes]. Ekaterinburg: Izd-vo Ural. un-ta, 279 p. (in Russ.).
Chernyshova, T. V. (2004). Faticheskoe obshchenie kak sotsial'nyy simvol kommunikatsii (na materiale tekstov pechatnykh SMI) [Phatic communication as a social symbol of communication (based on the texts of printed media]. Izvestiya Altayskogo gosudarstvennogo universiteta. Seriya istoriya, filologiya, filosofiya i pedagogika [The News of Altai State University], 4, pp. 46–51. (in Russ.).
Formanovskaya, N. I. (2006). Russkiy rechevoy etiket: lingvisticheskiy i metodicheskiy aspekty [Russian speech etiquette: linguistic and methodological aspects]. – Moscow: KomKniga, 160 p. (in Russ.).
Agrawal, A. (2016). Clickbait Detection using Deep Learning. 2nd IEEE International Conference on Next Generation Computing Technologies (NGCT). Dehradun, India, 14–16 October 2016, pp. 268–272. DOI: 10.1109/NGCT.2016.7877426.
Al Asaad, B. & Erascu, M. (2018). A tool for fake news detection. 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). Timisoara, Romania, 20–23 September 2018, pp. 379–386. DOI: 10.1109/SYNASC.2018.00064.
Anand, A., Chakraborty T. & Park N. (2017). We Used Neural Networks to Detect Clickbaits: You Won’t Believe What Happened Next! 39th European Conference on Information Retrieval (ECIR). Aberdeen, United Kingdom, 8–13 April 2017. Lecture Notes in Computer Science (LNCS), 10193, pp. 541–547. DOI: 10.1007/978-3-319-56608-5_46.
Daoud, D. M. & El-Seoud, M. S. A. (2019). An Effective Approach for Clickbait Detection Based on Supervised Machine Learning Technique. International Journal of Online and Biomedical Engineering (iJOE), 15(3), pp. 21–32. DOI: 10.3991/ijoe.v15i03.9843.
Fu, J., Liang, L., Zhou, X. & Zheng, J. (2017). A Convolutional Neural Network for Clickbait Detection. 4th International Conference on Information Science and Control Engineering (ICISCE). Changsha, China, 21–23 July 2017, pp. 6–10. DOI: 10.1109/ICISCE.2017.11.
Geckil, A., Mungen, A. A., Gundogan, E. & Kaya, M. (2018). A Clickbait Detection Method on News Sites. 10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). Barcelona, Spain, 28–31 August 2018, pp. 932–937. DOI: 10.1109/ASONAM.2018.8508452.
Jakobson, R. O. (1960). Closing Statements: Linguistics and Poetics. Sebeok, T. A. Style in Language. Cambridge: Massachusetts. Pp. 350–377.
Kępa-Figura, D. (2009). Intencje (czy intencja) nadawców medialnych, czyli fatyczność współczesnej komunikacji medialnej. Współczesne media. Status – Aksjologia – Funkcjonowanie. T. 1; red. I. Hofman & D. Kępa-Figura. Lublin: Wydawnictwo UMCS.
Kępa-Figura, D. (2010). Istota fatyczności a komunikacja medialna. Teorie komunikacji i mediów; red. M. Graszwicz & J. Jastrzębski. Wrocław: Wrocławskie Wydawnictwo Oświatowe. Pp. 89–100.
Khater, S. R., Al-Sahlee, O. H., Daoud, D. M. & El-Seoud, M. S. A. (2008). Clickbait Detection. 7th International Conference on Software and Information Engineering (ICSIE). British University in Cairo, Egypt, 2–4 May 2018. Pp. 111–115. DOI: 10.1145/3220267.3220287.
Malinowski, B. (1923). The problem of meaning in primitive languages. Ogden, C. K. & Richards, I. A. The meaning of meaning. New York: Harcourt. Brace & World. N.Y. Pp. 296–336.
Molyneux, L., Coddington, M. (2019). Aggregation, Clickbait and Their Effect on Perceptions of Journalistic Credibility and Quality. Journalism Practice. Taylor & Francis. DOI: 10.1080/17512786.2019.1628658.
Potthast, M., Köpsel, S., Stein, B. & Hagen, M. (2016). Clickbait Detection. 38th European Conference on Information Retrieval Research (ECIR). Padua, Italy, 20–23 March 2016. Lecture Notes in Computer Science (LNCS). Vol. 9626. Pp. 810–817. DOI: 10.1007/978-3-319-30671-1_72.
Prokofeva, N. & Shcheglova, E. (2021). Comic Reconsideration In Memes As The Means Of Social Relaxation. MSC 2020 International Scientific and Practical Conference “Man. Society. Communication”. Novgorod, Russia, 23–24 April 2020, available at: https://www.europeanproceedings.com/article/10.15405/epsbs.2021.05.02.35 (accessed: 18.10.2021). DOI: 10.15405/epsbs.2021.05.02.35.
Serrano, J. G., Romero-Rodríguez, L. M., Gómez, Á. H. (2018). Análisis del clickbaiting en los titulares de la prensa española contemporánea. Estudio de caso: diario El País en Facebook. Estudios Sobre el Mensaje Periodistico. Vol. 25, 1. Pp. 197–212. DOI: 10.5209/ESMP.63724.
Shu, K., Wang, S., Le, T., Lee, D. & Liu, H. (2018). Deep Headline Generation for Clickbait Detection. 8th IEEE International Conference on Data Mining (ICDM). Singapore, 17–20 November 2018. Pp. 467–476. DOI: 10.1109/ICDM.2018.00062.
Vasilieva V., Prokofeva, N. (2015). Slang Toponyms and Newsmakers’ Nicknames as a Communicative Contact and Indicator of Comic Culture in the Modern Russian Journalism. International Review of Management and Marketing. Vol. 5, No. 1S. Pp. 1–10.
Wang, S. & Wu, Q. (2018). An Empirical Study on the Clickbait of Data Science Articles in the WeChat Official Accounts. International Conference on Frontier Computing (FC). Osaka, Japan, 12–14 July 2017. Lecture Notes in Electrical Engineering (LNEE). Vol. 464. Pp. 131–140. DOI: 10.1007/978-981-10-7398-4_14.
Wongsap, N., Lou, L., Jumun, S., Prapphan, T., Kongyoung, S. & Kaothanthong, N. (2018). Thai Clickbait Headline News Classification and its Characteristic. International Conference on Embedded Systems and Intelligent Technology and International Conference on Information and Communication Technology for Embedded Systems (ICESIT-ICICTES). Khon Kaen, Thailand, 7–9 May 2018. Pp. 1–6. DOI: 10.1109/ICESIT-ICICTES.2018.8442064.
Zannettou, S., Chatzis, S. P., Papadamou, K. & Sirivianos, M. (2018). The Good, the Bad and the Bait: Detecting and Characterizing Clickbait on YouTube. 1st Deep Learning and Security Workshop, co-located with the 39th IEEE Symposium on Security and Privacy. San Francisco, 21–23 May 2018. Pp. 63–69. DOI: 10.1109/SPW.2018.00018.
Zheng, H.-T., Yao, X., Jiang, Y., Xia S.-T. & Xiao, X. (2017). Boost Clickbait Detection Based on User Behavior Analysis. 1st Asia-Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data (APWeb-WAIM). Beijing, China, 7–9 July 2017. Lecture Notes in Computer Science (LNCS). Vol. 10367. Pp. 73–80. DOI: 10.1007/978-3-319-63564-4_6.
Zheng, H.-T., Chen, J.-Y., Yao, X., Sangaiah, A. K., Jiang, Y. & Zhao, C.-Z. (2018). Clickbait Convolutional Neural Network. Symmetry. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/sym10050138.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Наталья Прокофьева, Ирина Акулович

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.





