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The Linguistic and Typological Features of Clickbait in Youtube Video Titles

   | 20 janv. 2023
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ALVES, L., ANTUNES, N., AGRICI, O., SOUSA, C., & RAMOS, C. (2016). Click Bait: You won’t believe what happens next!. Fronteiras: Journal of Social, Technological and Environmental Science, 5(2), 196–213. https://doi.org/10.21664/2238-8869.2016V5I2.P196-21310.21664/2238-8869.2016v5i2.p196-213 Search in Google Scholar

BIYANI, P., TSIOUTSIOULIKLIS, K., & BLACKMER, J. (2016, February 21). “8 Amazing secrets for getting more clicks”: Detecting clickbaits in news streams using article informality. [Conference proceedings]. Proceedings of the 13th AAAI Conference on Artificial Intelligence (pp. 94-100). AAAI-16, Phoenix, Arizona. AAAI Press. https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/11807/1156910.1609/aaai.v30i1.9966 Search in Google Scholar

BLOM, J. N. & HANSEN, K. R. (2014). Click bait: Forward-reference as lure in online news headlines. Journal of Pragmatics, 76, 87–100. https://doi.org/10.1016/j.pragma.2014.11.01010.1016/j.pragma.2014.11.010 Search in Google Scholar

CHAKRABORTY, A., PARANJAPE, A., SOURYA, K., & NILOY, G. (2016). Stop Clickbait: Detecting and preventing clickbaits in online news media”. [Conference proceedings]. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 9–16). 2016 IEEE, San Francisco, California. IEEE. https://doi.org/10.48550/arXiv.1610.0978610.1109/ASONAM.2016.7752207 Search in Google Scholar

CHEN, Y., CONROY, N. J., & RUBIN, V. L. (2015). Misleading online content: Recognising clickbait as “False News”. [Conference proceedings]. Proceedings of the 2015 ACM on Workshop on Multimodal Deception Detection (pp. 15-19). 2015 ACM, Seattle, Washington. ACM. https://doi.org/10.1145/2823465.282346710.1145/2823465.2823467 Search in Google Scholar

DEPRAETERE, I., & REED, S. (2020). Mood and modality in English. In B. Aarts, A. McMahon, & Hinrichs, L. (Eds), The Handbook of English Linguistics (pp. 269–290). Blackwell.10.1002/9781119540618.ch12 Search in Google Scholar

DOR, D. (2003). On newspaper headlines as relevance optimizers. Journal of Pragmatics, 35(5), 695–721. https://doi.org/10.1016/S0378-2166(02)00134-010.1016/S0378-2166(02)00134-0 Search in Google Scholar

ELYASHAR, A., BENDAHAN, J., & PUZIS, R. (2017). Detecting clickbait in online social media: You won’t believe how we did it. http://arxiv.org/abs/1710.06699 Search in Google Scholar

GENÇ, Ş., & SURER, E. (2021). ClickbaitTR: Dataset for clickbait detection from Turkish news sites and social media with a comparative analysis via machine learning algorithms. Journal of Information Science, 1–20. http://doi.org/10.1177/0165551521100774610.1177/01655515211007746 Search in Google Scholar

HANCOCK, J., & GONZALEZ, A. (2013). Deception in computer-mediated communication. In S. C. Herring, D. Stein, & T. Virtanen (Eds.), Pragmatics of Computer-Mediated Communication (pp. 363–383). De Gruyter Mouton.10.1515/9783110214468.363 Search in Google Scholar

IFANTIDOU, E. (2009). Newspaper headlines and relevance: ad hoc concepts in ad hoc contexts. Journal of Pragmatics, 41(4), 699–720. https://doi.org/10.1016/j.pragma.2008.10.01610.1016/j.pragma.2008.10.016 Search in Google Scholar

JIANG, T., GOU, Q., XU, Y., ZHAO, Y., & FU, S. (2019). What prompts users to click on news headlines? A click-stream data analysis of the effects of news recency and popularity. In N. G. Taylor, C. Christian-Lamb, M. H. Martin, & B. Nardi (Eds.), Information in Contemporary Society (pp. 539–546). Springer International Publishing.10.1007/978-3-030-15742-5_51 Search in Google Scholar

KUIKEN, J., SCHUTH, A., SPITTERS, M., & MARX, M. (2017). Effective headlines of newspaper articles in a digital environment. Digital Journalism, 5, 1300–1314. https://doi.org/10.1080/21670811.2017.127997810.1080/21670811.2017.1279978 Search in Google Scholar

LOCKWOOD, G. (2016). Academic clickbait: Articles with positively-framed titles, interesting phrasing, and no wordplay get more attention online. The Winnower, 3, 1–13. https://doi.org/10.15200/winn.146723.3633010.15200/winn.146723.36330 Search in Google Scholar

LOEWENSTEIN, G. (1994). The psychology of curiosity: A review and reinterpretation. Psychological Bulletin, 116(1), 75–98. https://psycnet.apa.org/doi/10.1037/0033-2909.116.1.7510.1037/0033-2909.116.1.75 Search in Google Scholar

LOPEZOSA, C., ORDUNA-MALEA, E., & PÉREZ-MONTORO, M. (2020). Making video news visible: Identifying the optimization strategies of the cybermedia on YouTube using web metrics. Journalism Practice, 14(4), 465–482. https://doi.org/10.1080/17512786.2019.162865710.1080/17512786.2019.1628657 Search in Google Scholar

MCCULLOCH, G. (2019). Because Internet: Understanding the New Rules of Language. Riverhead Books. Search in Google Scholar

MOLINA, M. D., SUNDAR, S.S., RONY, M.M.U., HASSAN, N., LE, T., & LEE, D. (2021). Does clickbait actually attract more clicks? Three clickbait studies you must read. [Conference proceedings]. In CHI Conference on Human Factors in Computing Science (pp. 1-19). CHI 2021, Yokohama, Japan. ACM. https://doi.org/10.1145/3411764.344575310.1145/3411764.3445753 Search in Google Scholar

MORMOL, P. (2019). “I urge you to see this...”. Clickbait as one of the dominant features of contemporary online headlines. Social Communication, 5(2), 1–10. http://dx.doi.org/10.2478/sc-2019-000410.2478/sc-2019-0004 Search in Google Scholar

MULLER, D. (2021, August 17). Clickbait is unreasonably effective. https://www.youtube.com/watch?v=S2x-HZPH5Sng Search in Google Scholar

OROSA, B. G., SANTORUN, S. G., & GARCÍA, X. L. (2017). Use of clickbait in the online news media of the 28 EU member countries. Revista Latina de Comunicación Social, 72, 1261–1277. https://doi.org/10.4185/RLCS-2017-1218en10.4185/RLCS-2017-1218en Search in Google Scholar

POTTHAST, M., GOLLUB, T., KOMOLOSSY, K., SCHUSTER, S., WEIGMANN, M., FERNANDEZ, E.P.G., HAGEN, M., & STEIN, B. (2018). Crowdsourcing a large corpus of clickbait on Twitter. [Conference proceedings]. In Proceedings of the 27th International Conference on Computational Linguistics (pp. 1498–1507). ICCL 2018, Santa Fe, New Mexico. ICCL. Search in Google Scholar

POTTHAST, M., KÖPSEL, S., STEIN, B. AND HAGAN, M. (2016). Clickbait detection. In Information Retrieval (pp. 810–817). [Conference proceedings]. European Conference on Information Retrieval, Padua, Italy. Springer International Publishing.10.1007/978-3-319-30671-1_72 Search in Google Scholar

QU, J., HIΒBACH, A.M., GOLLUB, T., & POTTHAST, M. (2018). Towards crowdsourcing clickbait labels for You-Tube videos. [Conference proceedings]. In Proceedings of the The 6th AAAI Conference on Human Computation and Crowdsourcing (pp. 1–4). HCOMP 2018, Zürich: CEUR-WS. Search in Google Scholar

RONY, M. M. U., HASSAN, N. AND YOUSUF, M. (2017). Diving deep into clickbaits: Who use them to what extents in which topics with what effects?. [Conference proceedings]. In Proceedings of the 2017 IEEE/ACM International Conference (pp. 232–239). 2017 IEEE/ACM International Conference, Sydney, Australia, ACM.10.1145/3110025.3110054 Search in Google Scholar

SADRI, S. R. (2019). Listicles and the modern news article: comparing the perceived credibility of listicles and traditional articles among millennial media consumers. Atlantic Journal of Communication, 27(2), 83–98. https://doi.org/10.1080/15456870.2019.157479410.1080/15456870.2019.1574794 Search in Google Scholar

SCOTT, K. (2021). You won’t believe what’s in this paper! Clickbait, relevance and the curiosity gap. Journal of Pragmatics, 175, 53–66. https://doi.org/10.1016/j.pragma.2020.12.02310.1016/j.pragma.2020.12.023 Search in Google Scholar

SPERBER, D., & WILSON, D. (1995). Relevance: Communication and cognition. Blackwell. Search in Google Scholar

SPERBER, D., & WILSON, D. (2008). A deflationary account of metaphors. In R.W. Gibbs (Ed.), The Cambridge Handbook of Metaphor and Thought (pp. 84–105). Cambridge University Press.10.1017/CBO9780511816802.007 Search in Google Scholar

TAFESSE, W. (2020). YouTube marketing: How marketers’ video optimisation practices influence video views. Internet Research, 30(6), 1689–1707. https://doi.org/10.1108/INTR-10-2019-040610.1108/INTR-10-2019-0406 Search in Google Scholar

VARSHNEY, D., & VISHWAKARMA, D. K. (2021). A unified approach for detection of clickbait videos on YouTube using cognitive evidence. Applied Intelligence, 51, 4214–4235. https://doi.org/10.1007/s10489-020-02057-910.1007/s10489-020-02057-9 Search in Google Scholar

VIJGEN, B. (2014). The listicle: an exploring research on an interesting sharable new media phenomenon. Studia Universitatis Babes-Bolyai – Ephemerides, 59(1), 103–122. http://studia.ubbcluj.ro/download/pdf/894.pdf Search in Google Scholar

ZANNETTOU, S., CHATZIS, S., PAPADAMOU, K., & SIRIVIANOS, M. (2018). The good, the bad and the bait: Detecting and characterising clickbait on YouTube. In Security and Privacy Workshops (pp. 63–69). [Symposium]. IEEE Symposium on Security and Privacy Workshops, San Francisco, California.10.1109/SPW.2018.00018 Search in Google Scholar