Does clickbait actually atract more clicks? three clickbait studies you must read

Maria D. Molina, S. Shyam Sundar, Md Main Uddin Rony

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Studies show that users do not reliably click more often on headlines classifed as clickbait by automated classifers. Is this because the linguistic criteria (e.g., use of lists or questions) emphasized by the classifers are not psychologically relevant in attracting interest, or because their classifcations are confounded by other unknown factors associated with assumptions of the classifers? We address these possibilities with three studies-a quasi-experiment using headlines classifed as clickbait by three machine-learning models (Study 1), a controlled experiment varying the headline of an identical news story to contain only one clickbait characteristic (Study 2), and a computational analysis of four classifers using real-world sharing data (Study 3). Studies 1 and 2 revealed that clickbait did not generate more curiosity than non-clickbait. Study 3 revealed that while some headlines generate more engagement, the detectors agreed on a classifcation only 47% of the time, raising fundamental questions about their validity.

Original languageEnglish (US)
Title of host publicationCHI 2021 - Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationMaking Waves, Combining Strengths
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450380966
DOIs
StatePublished - May 6 2021
Event2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021 - Virtual, Online, Japan
Duration: May 8 2021May 13 2021

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021
Country/TerritoryJapan
CityVirtual, Online
Period5/8/215/13/21

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

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