Click me…! The influence of clickbait on user engagement in social media and the role of digital nudging
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Clickbait to make people click on a linked article is commonly used on social media. We analyze the impact of clickbait on user interaction on Facebook in the form of liking, sharing and commenting. For this, we use a data set of more than 4,400 Facebook posts from 10 different news sources to analyze how clickbait in post headlines and in post text influences user engagement. The results of our study revealed that certain features (e.g., unusual punctuation and common clickbait phrases) increase user interaction, whereas others decrease engagement with Facebook posts. We further use our results to discuss the potential role of digital nudging in the context of clickbait. Our results contribute to understanding and making use of the effect of different framings in social media.
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Some clickbait features can increase user interaction, and sensational features can be associated with engagement on social platforms.
“It also aligns with research showing that some clickbait features can increase user interaction (Jung et al., 2022;Kuiken et al., 2017) and that sensational features can be associated with engagement on social platforms (Khawar & Boukes, 2025).”
From Sensational Headlines, Engagement, and Credibility in Nepal’s Online News (2025) · cites this paper as Jung et al., 2022
Studies of clickbait and sensationalism suggest that some headline features can increase user interaction, but the effect is uneven, context-dependent, and often accompanied by reputational risk.
“Studies of clickbait and sensationalism suggest that some headline features can increase user interaction, but the effect is uneven, context-dependent, and often accompanied by reputational risk (Jácobo-Morales, & Marino-Jiménez, 2024;Jung et al., 2022;Khawar & Boukes, 2025;Kuiken et al., 2017).”
From Sensational Headlines, Engagement, and Credibility in Nepal’s Online News (2025) · cites this paper as Jung et al., 2022
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VADER: a parsimonious rule-based model for sentiment analysis of social media text
Hutto, C., & Gilbert, E. (2014) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v8i1.14550 · Cited by 6,087 · see citing works
What is user engagement? A conceptual framework for defining user engagement with technology
O'Brien, H. L., & Toms, E. G. (2008) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20801 · Cited by 1,397 · see citing works
Using VADER sentiment and SVM for predicting customer response sentiment
Borg, A., & Boldt, M. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113746 · Cited by 251 · see citing works
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Research works printed but not linked: 77
- [1]Newman N, Fletcher R, Levy DAL, Nielsen RK. Reuters Institute Digital News Report 2016. Reuters Institute for the Study of Journalism, University of Oxford. 2016.
- [2]Camarero C, Garrido M-J, San Jose R. What Works in Facebook Content Versus Relational Communication: A Study of their Effectiveness in the Context of Museums. Int J Human–Computer Interact. 2018; 34: 1119– 1134. doi: 10.1080/10447318.2017.1418475 · DOI
- [3]Lowenstein-Barkai H, Lev-On A. Complementing or Substituting? News in an Era of Multiple Platforms and Second Screens. Int J Human–Computer Interact. 2018; 34: 922– 931. doi: 10.1080/10447318.2018.1471571 · DOI
- [4]Müller P, Schneiders P, Schäfer S. Appetizer or main dish? Explaining the use of Facebook news posts as a substitute for other news sources. Comput Human Behav. 2016; 65: 431– 441. doi: 10.1016/j.chb.2016.09.003 · DOI
- [5]Roberts JA, David ME. The Social Media Party: Fear of Missing Out (FoMO), Social Media Intensity, Connection, and Well-Being. Int J Human–Computer Interact. 2020; 36: 386– 392. doi: 10.1080/10447318.2019.1646517 · DOI · Paper page
- [6]Hansen PG, Jespersen AM. Nudge and the manipulation of choice: A framework for the responsible use of the nudge approach to behaviour change in public policy. Eur J Risk Regul. 2013; 4: 3– 28. doi: 10.1017/s1867299x00002762 · DOI
- [7]Kahai SS, Lei Y. Building social capital with Facebook: Type of network, availability of other media, and social self-efficacy matter#. Int J Hum Comput Stud. 2019; 130: 113– 129. doi: 10.1016/j.ijhcs.2019.05.013 · DOI
- [9]Ju A, Jeong SH, Chyi HI. Will Social Media Save Newspapers? Journal Pract. 2014; 8: 1– 17. doi: 10.1080/17512786.2013.794022 · DOI
- [10]Nuaim A Al, Yim D, Khuntia J. Subjectivity and online news sharing. AMCIS 2017—America’s Conference on Information Systems: A Tradition of Innovation. Boston, USA; 2017.
- [11]Potthast M, Köpsel S, Stein B, Hagen M. Clickbait Detection. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2016. pp. 810– 817. doi: 10.1007/978-3-319-30671-1_72 · DOI
- [12]Pengnate S. Measuring emotional arousal in clickbait: Eye-tracking approach. AMCIS 2016: Surfing the IT Innovation Wave - 22nd Americas Conference on Information Systems. 2016. pp. 1– 9.
- [13]Felle T. Digital watchdogs? Data reporting and the news media’s traditional ‘fourth estate’ function. Journal Theory, Pract Crit. 2016; 17: 85– 96. doi: 10.1177/1464884915593246 · DOI
- [14]Nai A. The fourth estate. Election Watchdogs: Transparency, Accountability and Integrity. 2017. pp. 191– 210. doi: 10.1093/acprof:oso/9780190677800.003.0010 · DOI
- [15]Bakir V, McStay A. Fake News and The Economy of Emotions: Problems, causes, solutions. Digit Journal. 2018; 6: 154– 175. doi: 10.1080/21670811.2017.1345645 · DOI
- [16]Richardson N. Fake News and Journalism Education. Asia Pacific Media Educator. 2017. pp. 1– 9. doi: 10.1177/1326365X17702268 · DOI
- [17]Rubin VL, Chen Y, Conroy NJ. Deception detection for news: Three types of fakes. Proc Assoc Inf Sci Technol. 2015; 52: 1– 4. doi: 10.1002/pra2.2015.145052010083 · DOI
- [18]Kalsnes B, Larsson AO. Understanding News Sharing Across Social Media: Detailing distribution on Facebook and Twitter. Journalism Studies. 2017: 1– 20. doi: 10.1080/1461670X.2017.1297686 · DOI
- [19]Stokowiec W, Trzciński T, Wołk K, Marasek K, Rokita P. Shallow reading with deep learning: Predicting popularity of online content using only its title. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2017. pp. 136– 145. doi: 10.1007/978-3-319-60438-1_14 · DOI
- [20]Otto L, Glogger I, Boukes M. The Softening of Journalistic Political Communication: A Comprehensive Framework Model of Sensationalism, Soft News, Infotainment, and Tabloidization. Commun Theory. 2017; 27: 136– 155. doi: 10.1111/comt.12102 · DOI
- [21]Uddin Rony MM, Hassan N, Yousuf M. Diving deep into clickbaits: Who use them to what extents in which topics with what effects? Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. New York, New York, USA: ACM Press; 2017. pp. 232– 239. doi: 10.1145/3110025.3110054 · DOI
- [24]Cotter C. SPJ Code of Ethics. In: News Talk. 2012 pp. 251– 251. doi: 10.1017/cbo9780511811975.016 · DOI
- [25]Molyneux L, Coddington M. Aggregation, Clickbait and Their Effect on Perceptions of Journalistic Credibility and Quality. Journal Pract. 2020; 14: 429– 446. doi: 10.1080/17512786.2019.1628658 · DOI
- [27]Lu H, Zhang M, Ma S. Between clicks and satisfaction: Study on multi-phase user preferences and satisfaction for online news reading. 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. New York, New York, USA: ACM Press; 2018. pp. 435– 444. doi: 10.1145/3209978.3210007 · DOI
- [28]Thaler RH, Sunstein CR. Nudge. Int’l. London, GB: Penguin Books; 2009.
- [29]Weinmann M, Schneider C, vom Brocke J. Digital Nudging. Bus Inf Syst Eng. 2016; 58: 433– 436. doi: 10.1007/s12599-016-0453-1 · DOI
- [30]Vargheese JP, Sripada S, Masthoff J, Oren N. Persuasive Strategies for Encouraging Social Interaction for Older Adults. Int J Hum Comput Interact. 2016; 32: 190– 214. doi: 10.1080/10447318.2016.1136176 · DOI
- [31]Rudat A, Buder J, Hesse FW. Audience design in Twitter: Retweeting behavior between informational value and followers’ interests. Comput Human Behav. 2014; 35: 132– 139. doi: 10.1016/j.chb.2014.03.006 · DOI
- [32]Deuze M, Bruns A, Neuberger C. Preparing for an age of participatory news. Journal Pract. 2007; 1: 322– 338. doi: 10.1080/17512780701504864 · DOI
- [33]Leonhard L, Karnowski V, Kümpel AS. Online and (the feeling of being) informed: Online news usage patterns and their relation to subjective and objective political knowledge. Comput Human Behav. 2020; 103: 181– 189. doi: 10.1016/j.chb.2019.08.008 · DOI
- [34]Glenberg AM, Wilkinson AC, Epstein W. The illusion of knowing: Failure in the self-assessment of comprehension. Mem Cognit. 1982; 10: 597– 602. doi: 10.3758/BF03202442 · DOI
- [35]Pearson GD, Knobloch-Westerwick S. Perusing pages and skimming screens: Exploring differing patterns of selective exposure to hard news and professional sources in online and print news. New Media Soc. 2018; 20: 3580– 3596. doi: 10.1177/1461444818755565 · DOI
- [36]Hermida A, Lewis SC, Zamith R. Sourcing the Arab Spring: A Case Study of Andy Carvin’s Sources on Twitter During the Tunisian and Egyptian Revolutions. J Comput Commun. 2014; 19: 479– 499. doi: 10.1111/jcc4.12074 · DOI
- [37]Khare P, Torres P, Heravi BR. What Just Happened? A Framework for Social Event Detection and Contextualisation. Hawaii International Conference on System Sciences (HICSS). IEEE; 2015. pp. 1565– 1574. doi: 10.1109/HICSS.2015.190 · DOI
- [38]Tandoc EC. Journalism is twerking? How web analytics is changing the process of gatekeeping. New Media Soc. 2014; 16: 559– 575. doi: 10.1177/1461444814530541 · DOI
- [39]Hanusch F, Tandoc EC. Comments, analytics, and social media: The impact of audience feedback on journalists’ market orientation. Journal Theory, Pract Crit. 2017; 146488491772030. doi: 10.1177/1464884917720305 · DOI
- [40]Chen Y, Conroy NJ, Rubin VL. Misleading online content: Recognizing clickbait as “false news.” WMDD 2015—Proceedings of the ACM Workshop on Multimodal Deception Detection, co-located with ICMI 2015. 2015. pp. 15– 19. doi: 10.1145/2823465.2823467 · DOI
- [42]Willis J. The mind of a journalist: How reporters view themselves, their world, and their craft. The Mind of a Journalist: How Reporters View Themselves, Their World, and Their Craft. 2010. doi: 10.4135/9781452274911 · DOI
- [43]Johnson TJ, Kaye BK. Webelievability: A path model examining how convenience and reliance predict online credibility. Journal Mass Commun Q. 2002; 79: 619– 642. doi: 10.1177/107769900207900306 · DOI
- [44]Cable J, Mottershead G. “Can I click it? Yes you can”: Football journalism, Twitter, and clickbait. Ethical Sp Int J Commun Ethics. 2018; 15: 69– 80.
- [45]Fico F, Richardson JD, Edwards SM. Influence of Story Structure on Perceived Story Bias and News Organization Credibility. Mass Commun Soc. 2004; 7: 301– 318. doi: 10.1207/s15327825mcs0703_3 · DOI
- [46]García Orosa B, Gallur Santorun S, López García X. El uso del clickbait en cibermedios de los 28 países de la Unión Europea. Rev Lat Comun Soc. 2017; 72: 1261– 1277. doi: 10.4185/RLCS-2017-1218 · DOI
- [47]Lischka JA, Garz M. Clickbait news and algorithmic curation: A game theory framework of the relation between journalism, users, and platforms. New Media Soc. 2021 [cited 9 Jan 2022]. doi: 10.1177/14614448211027174 · DOI
- [48]Palau-Sampio D. Reference press metamorphosis in the digital context: clickbait and tabloid strategies in Elpais.com. Commun Soc. 2016; 29: 63– 79. doi: 10.15581/003.29.2.63–79 · DOI
- [49]Blom JN, Hansen KR. Click bait: Forward-reference as lure in online news headlines. J Pragmat. 2015; 76: 87– 100. doi: 10.1016/j.pragma.2014.11.010 · DOI · Paper page
- [50]Lefkowitz J. “Tabloidization” or Dual-Convergence: Quoted speech in tabloid and “quality” British newspapers 1970–2010. Journal Stud. 2018; 19: 353– 375. doi: 10.1080/1461670X.2016.1190662 · DOI
- [51]Ecker UKH, Lewandowsky S, Chang EP, Pillai R. The effects of subtle misinformation in news headlines. J Exp Psychol Appl. 2014; 20: 323– 335. doi: 10.1037/xap0000028 25347407 · DOI
- [52]Kuiken J, Schuth A, Spitters M, Marx M. Effective Headlines of Newspaper Articles in a Digital Environment. Digit Journal. 2017; 5: 1300– 1314. doi: 10.1080/21670811.2017.1279978 · DOI · Paper page
- [53]Scacco JM, Muddiman A. The curiosity effect: Information seeking in the contemporary news environment. New Media Soc. 2019. doi: 10.1177/1461444819863408 · DOI
- [54]Shostak GI, Gillespie D. Communicative Tactics of Creating Headlines in British Newspapers. Procedia—Soc Behav Sci. 2014; 154: 276– 279. doi: 10.1016/j.sbspro.2014.10.151 · DOI
- [56]Molek-Kozakowska K. Towards a pragma-linguistic framework for the study of sensationalism in news headlines. Discourse Commun. 2013; 7: 173– 197. doi: 10.1177/1750481312471668 · DOI · Paper page
- [57]Biyani P, Tsioutsiouliklis K, Blackmer J. “8 Amazing Secrets for Getting More Clicks”: Detecting Clickbaits in News Streams Using Article Informality Clickbait classification. Proceedings of the 30th AAAI Conference on Artifical Intelligence (AAAI-16). 2016. pp. 94– 100.
- [58]Chakraborty A, Paranjape B, Kakarla S, Ganguly N. Stop Clickbait: Detecting and preventing clickbaits in online news media. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2016. pp. 9– 16. doi: 10.1109/ASONAM.2016.7752207 · DOI · Paper page
- [59]Petty R., Cacioppo J. The elaboration likelihood model of persuasion. Adv Exp Soc Psychol. 1986; 19: 123– 205. doi: 10.1558/ijsll.v14i2.309 · DOI
- [60]Meske C, Potthoff T. The DINU-Model–A Process Model for the Design of Nudges. European Conference on Information Systems (ECIS). Guimarães, Portugal; 2017. pp. 2587– 2597.
- [61]Spagnolli A, Chittaro L, Gamberini L. Interactive Persuasive Systems: A Perspective on Theory and Evaluation. Int J Hum Comput Interact. 2016; 32: 177– 189. doi: 10.1080/10447318.2016.1142798 · DOI
- [62]Freyne J, Yin J, Brindal E, Hendrie GA, Berkovsky S, Noakes M. Push Notifications in Diet Apps: Influencing Engagement Times and Tasks. Int J Hum Comput Interact. 2017; 33: 833– 845. doi: 10.1080/10447318.2017.1289725 · DOI
- [63]Wisniewski PJ, Knijnenburg BP, Lipford HR. Making privacy personal: Profiling social network users to inform privacy education and nudging. Int J Hum Comput Stud. 2017; 98: 95– 108. doi: 10.1016/j.ijhcs.2016.09.006 · DOI
- [64]Khern-Am-Nuai W, Yang W, Li N. Using context-based password strength meter to nudge users’ password generating behavior: A randomized experiment. Proceedings of the Annual Hawaii International Conference on System Sciences. 2017. pp. 587– 596. doi: 10.24251/hicss.2017.071 · DOI
- [65]van Bavel R, Rodríguez-Priego N, Vila J, Briggs P. Using protection motivation theory in the design of nudges to improve online security behavior. Int J Hum Comput Stud. 2019; 123: 29– 39. doi: 10.1016/j.ijhcs.2018.11.003 · DOI
- [66]Renaud K, Zimmermann V. Ethical guidelines for nudging in information security & privacy. Int J Hum Comput Stud. 2018; 120: 22– 35. doi: 10.1016/j.ijhcs.2018.05.011 · DOI
- [67]Djurica D, Figl K. The effect of digital nudging techniques on customers’ product choice and attitudes towards e-commerce sites. AMCIS 2017—America’s Conference on Information Systems: A Tradition of Innovation. 2017. pp. 1– 5.
- [68]Bhuiyan MM, Vick K, Mitra T, Zhang K, Horning MA. FeedReflect: A tool for nudging users to assess news credibility on twitter. Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. New York, New York, USA: ACM Press; 2018. pp. 205– 208. doi: 10.1145/3272973.3274056 · DOI
- [69]Kroll T, Stieglitz S. Digital nudging and privacy: improving decisions about self-disclosure in social networks. Behav Inf Technol. 2021; 40: 1– 19. doi: 10.1080/0144929X.2019.1584644 · DOI
- [70]Thaler RH. Nudge, not sludge. Science. 2018. p. 431. doi: 10.1126/science.aau9241 30072515 · DOI
- [71]Neuberger C, Kapern P. Grundlagen des Journalismus. Grundlagen des Journalismus. Wiesbaden: Springer Fachmedien Wiesbaden; 2013. doi: 10.1007/978-3-531-94191-2 · DOI
- [72]Hull M. News Feed FYI: Bringing People Closer Together. Facebook Newsroom. 2018. pp. 1– 3.
- [73]Ross B, Potthoff T, Majchrzak TA, Chakraborty NR, Lazreg M Ben, Stieglitz S. The diffusion of crisis-related communication on social media: An empirical analysis of Facebook reactions. Proceedings of the Annual Hawaii International Conference on System Sciences. 2018. pp. 2525– 2534. doi: 10.24251/hicss.2018.319 · DOI
- [74]Chakraborty A, Sarkar R, Mrigen A, Ganguly N. Tabloids in the era of social media? Understanding the production and consumption of clickbaits in Twitter. Proc ACM Human-Computer Interact. 2017; 1. doi: 10.1145/3134665 · DOI
- [75]Chakraborty A, Paranjape B, Kakarla S, Ganguly N. Stop Clickbait: Detecting and preventing clickbaits in online news media. Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. 2016. pp. 9– 16. doi: 10.1109/ASONAM.2016.7752207 · DOI · Paper page
- [77]Pano T, Kashef R. A complete vader-based sentiment analysis of bitcoin (BTC) tweets during the ERA of COVID-19. Big Data Cogn Comput. 2020; 4: 1– 17. doi: 10.3390/bdcc4040033 · DOI
- [78]Elbagir S, Yang J. Twitter sentiment analysis using natural language toolkit and Vader sentiment. Lect Notes Eng Comput Sci. 2019; 2239: 12– 16. Available: http://www.iaeng.org/publication/IMECS2019/IMECS2019_pp12-16.pdf.
- [81]Reinemann C, Stanyer J, Scherr S, Legnante G. Hard and soft news: A review of concepts, operationalizations and key findings. Journalism. 2012. pp. 221– 239. doi: 10.1177/1464884911427803 · DOI
- [82]Landis JR, Koch GG. The Measurement of Observer Agreement for Categorical Data. Biometrics. 1977; 33: 159. doi: 10.2307/2529310 843571 · DOI · Paper page
- [83]Hilbe JM. Negative binomial regression. Negative Binomial Regression. Cambridge, United Kingdom: Cambridge University Press; 2007. doi: 10.1017/CBO9780511811852 · DOI
- [84]Vergeer M, Hermans L. Campaigning on Twitter: Microblogging and Online Social Networking as Campaign Tools in the 2010 General Elections in the Netherlands. J Comput Commun. 2013; 18: 399– 419. doi: 10.1111/jcc4.12023 · DOI
- [85]Thompson N, Wang X, Daya P. Determinants of News Sharing Behavior on Social Media. J Comput Inf Syst. 2020; 60: 593– 601. doi: 10.1080/08874417.2019.1566803 · DOI
- [86]Prior M. Any good news in soft news? The impact of soft news preference on political knowledge. Political Communication. 2003. pp. 149– 171. doi: 10.1080/10584600390211172 · DOI
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Sensational Headlines, Engagement, and Credibility in Nepal’s Online News
Dahal, S. (2025) · Nepalese Journal of Development and Rural Studies · doi:10.3126/njdrs.v22i1.99390
- Authors
- Jung, A.-K., Stieglitz, S., Kissmer, T., Mirbabaie, M., & Kroll, T.
- Affiliations
- University of Duisburg-Essen (DE)
- Paderborn University (DE)
- Corresponding author
- Jung, Anna-Katharina
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2022-06-29
- Volume
- 17
- Issue
- 6
- Pages
- e0266743
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC9242456
- OpenAlex
- W4285414158
- Cited by
- 64
- References
- 3
- Citations by year
- 2026: 18 · 2025: 20 · 2024: 18 · 2023: 7 · 2022: 1
- FWCI
- 14.57
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Universitätsbibliographie, Universität Duisburg-Essen (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DuEPublico (University of Duisburg-Essen) (submittedVersion, cc-by)
- Funders
- Open Access Publication Fund of the University XY
- Topics
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Physical Sciences › Computer Science › Computer Science Applications › Digital Media and Philosophy
- Keywords
- clickbait, user engagement, social media, Facebook, digital nudging, news headlines, framing effects, news sources
- MeSH terms
- Emotions, Humans, Text Messaging, Social Media
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