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The Antecedents and Rebroadcast Consequences of Clickbait

Prithwiraj Mukherjee, Souvik Dutta and Dalhia Mani
2019
Working Paper No
592
Body

Clickbait is a method of framing articles' titles to induce readers to click on them, and is a common feature of online media today. We use a publicly available data set consisting of articles from 25 media organizations, each of which is rated as clickbait or not by human respondents, and augment it with Twitter retweet count, sentiment analysis and topic modeling. We demonstrate that human interest articles are positively associated with clickbait. We also show that the fraction of people with journalistic backgrounds in an organization's top management team is positively related to its clickbait usage. Finally we show that clickbait is rebroadcast less than non-clickbait on social media. Our results serve as a cautionary message to  media organizations and  digital marketers, who may be inadvertently harming the reach of their content by using clickbait.

Key words
Clickbait, Sharing, Upper Echelons Theory, Sentiment Analysis, Latent Dirichlet Allocation, Propensity Score Matching
WP No. 592.pdf (924.36 KB)

The Antecedents and Rebroadcast Consequences of Clickbait

Author(s) Name: Prithwiraj Mukherjee, Souvik Dutta and Dalhia Mani, 2019
Working Paper No : 592
Abstract:

Clickbait is a method of framing articles' titles to induce readers to click on them, and is a common feature of online media today. We use a publicly available data set consisting of articles from 25 media organizations, each of which is rated as clickbait or not by human respondents, and augment it with Twitter retweet count, sentiment analysis and topic modeling. We demonstrate that human interest articles are positively associated with clickbait. We also show that the fraction of people with journalistic backgrounds in an organization's top management team is positively related to its clickbait usage. Finally we show that clickbait is rebroadcast less than non-clickbait on social media. Our results serve as a cautionary message to  media organizations and  digital marketers, who may be inadvertently harming the reach of their content by using clickbait.

Keywords: Clickbait, Sharing, Upper Echelons Theory, Sentiment Analysis, Latent Dirichlet Allocation, Propensity Score Matching
WP No. 592.pdf (924.36 KB)