{"title":"Are You What You Tweet? The Impact of Sentiment on Digital News Consumption and Social Media Sharing","authors":"Hyelim Oh, K. Goh, T. Phan","doi":"10.2139/ssrn.3215634","DOIUrl":null,"url":null,"abstract":"This study examines the impact of news content sentiment on digital news readership and social media sharing. Using econometric analyses and models estimated with rich clickstream data on online news readership and social media sharing data collected from Twitter, we find a differential effect of sentiment on news readership and sharing behaviors. Specifically, individuals are likely to read news articles with negative headline sentiment on the news website but tend to share articles with positive article sentiment on Twitter. Upon decomposition of news article sentiment, we find a contrasting positive author sentiment effect and a negative news topic valence effect on news readership. Interestingly, we uncover that an increase in a Twitter user’s followers leads to an increase in the Twitter user’s propensity to share positive-sentiment news articles. Overall, our findings affirm the coopetitive 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. Importantly, given the dichotomy between news reading and sharing behaviors, predicting individual behaviors based on social media opinions may need to be viewed with prudence.","PeriodicalId":301794,"journal":{"name":"Communication & Computational Methods eJournal","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communication & Computational Methods eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3215634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This study examines the impact of news content sentiment on digital news readership and social media sharing. Using econometric analyses and models estimated with rich clickstream data on online news readership and social media sharing data collected from Twitter, we find a differential effect of sentiment on news readership and sharing behaviors. Specifically, individuals are likely to read news articles with negative headline sentiment on the news website but tend to share articles with positive article sentiment on Twitter. Upon decomposition of news article sentiment, we find a contrasting positive author sentiment effect and a negative news topic valence effect on news readership. Interestingly, we uncover that an increase in a Twitter user’s followers leads to an increase in the Twitter user’s propensity to share positive-sentiment news articles. Overall, our findings affirm the coopetitive 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. Importantly, given the dichotomy between news reading and sharing behaviors, predicting individual behaviors based on social media opinions may need to be viewed with prudence.