Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/22428
Title: Did clickbait crack the code on virality?
Authors: Mukherjee, Prithwiraj 
Dutta, Souvik 
De Bruyn, Arnaud 
Keywords: Clickbait;Persuasion Knowledge Model;Propensity score matching;Sentiment analysis;Sharing;Social media;Source derogation;Topic modeling
Issue Date: 2022
Publisher: Springer
Abstract: Although clickbait is a ubiquitous tactic in digital media, we challenge the popular belief that clickbait systematically leads to enhanced sharing of online content on social media. Using the Persuasion Knowledge Model, we predict that clickbait tactics may be perceived by some readers as a manipulative attempt, leading to source derogation where the publisher may be perceived as less competent and trustworthy. This, in turn, may reduce some readers’ intention to share content. Using a controlled experiment, we confirm that high-emotional headlines are shared more and show evidence that clickbait often leads to inferences of manipulative intent and source derogation. We then use a well-known secondary data set containing 19,386 articles from 27 leading online publishers. We supplement it with Twitter share data, sentiment analysis, topic modeling, and additional control variables. We confirm that, on average, clickbait articles elicit far fewer shares than non-clickbait articles. Our results are stable, with large effect sizes even after controlling for endogenous selection. © 2021, Academy of Marketing Science.
URI: https://repository.iimb.ac.in/handle/2074/22428
ISSN: 1552-7824
0092-0703
DOI: 10.1007/s11747-021-00830-x
Appears in Collections:2020-2029 C

Show full item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.