Are You What You Tweet? The Impact of Sentiment on Digital News Consumption and Social Media Sharing
72 Pages Posted: 7 Aug 2018 Last revised: 1 Feb 2021
Date Written: July 17, 2018
While social media has helped online newspapers by allowing users to organically share articles, some have argued that it has cannibalised and hurt newspapers through reduced readership and diminished agenda-setting power. Motivated by these two opposing effects, it is critical to understand what affects the duality between sharing news articles on social media and reading the articles on news websites. Using rich clickstream data on online news readership obtained from an English newspaper in an Asian country and social media data collected from Twitter, we focus on article sentiment as a key news content attribute and find a differential effect of sentiment on readership and sharing behaviours across the news site and third-party social media platform. Our results show that people are likely to read news articles with negative sentiment on the news site, but tend to share articles with positive sentiment on Twitter. Specifically, a 1-percent increase in content sentiment is associated with a 2.15-percent decrease in news site page views, but a 0.76-percent increase in Twitter sharing volume. Upon decomposition of news article sentiment, we also find a contrasting positive author sentiment effect and a negative news topic valence effect on news readership. To uncover the underlying mechanism of the findings, we test the key intuitions from prior self-presentation literature. We find that an increase in a Twitter user’s followers (i.e., audience size) leads to an increase in the Twitter user’s propensity to share positive-sentiment news articles. Our findings on the role of sentiment on content consumption and sharing affirm the co-opetitive but complementary relationship between news websites and social media platforms. Our results also guide publishers to better craft their news content and manage social media presence to improve audience engagement and readership outcomes while preserving the agenda-setting ability of news media.
Keywords: digital content, social media, news media, sentiment, self-presentation, text mining
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