Breaking the News: First Impressions Matter on Online News

A growing number of people are changing the way they consume news, replacing the traditional physical newspapers and magazines by their virtual online versions or/and weblogs. The interactivity and immediacy present in online news are changing the way news are being produced and exposed by media corporations. News websites have to create effective strategies to catch people's attention and attract their clicks. In this paper we investigate possible strategies used by online news corporations in the design of their news headlines. We analyze the content of 69,907 headlines produced by four major global media corporations during a minimum of eight consecutive months in 2014. In order to discover strategies that could be used to attract clicks, we extracted features from the text of the news headlines related to the sentiment polarity of the headline. We discovered that the sentiment of the headline is strongly related to the popularity of the news and also with the dynamics of the posted comments on that particular news.

[1]  Pablo J. Boczkowski,et al.  Between tradition and change , 2009 .

[2]  Jisun An,et al.  Understanding News Geography and Major Determinants of Global News Coverage of Disasters , 2014, ArXiv.

[3]  Kalev Leetaru,et al.  Culturomics 2.0: Forecasting large-scale human behavior using global news media tone in time and space , 2011, First Monday.

[4]  Kate Sweeny,et al.  Do You Want the Good News or the Bad News First ? News Order Influences Recipients ’ Mood , Perceptions , and Behaviors , 2011 .

[5]  Michele Coscia,et al.  Average is Boring: How Similarity Kills a Meme's Success , 2014, Scientific Reports.

[6]  D. Domingo,et al.  Making Online News: The ethnography of new media production, 1 , 2008 .

[7]  Sotiris Ioannidis,et al.  we.b: the web of short urls , 2011, WWW.

[8]  Daniel Riffe,et al.  Mood Influence on the Appeal of Bad News , 1994 .

[9]  Lars Kai Hansen,et al.  Good Friends, Bad News - Affect and Virality in Twitter , 2011, ArXiv.

[10]  Frank Hopfgartner,et al.  Users' reading habits in online news portals , 2014, IIiX.

[11]  Jure Leskovec,et al.  How Community Feedback Shapes User Behavior , 2014, ICWSM.

[12]  Krishna P. Gummadi,et al.  Sharing political news: the balancing act of intimacy and socialization in selective exposure , 2014, EPJ Data Science.

[13]  Ron Kohavi,et al.  Guest Editors' Introduction: On Applied Research in Machine Learning , 1998, Machine Learning.

[14]  Jon M. Kleinberg,et al.  Does Bad News Go Away Faster? , 2011, ICWSM.

[15]  Justin M. Rao,et al.  Fair and Balanced? Quantifying Media Bias through Crowdsourced Content Analysis , 2016 .

[16]  Ullrich K. H. Ecker,et al.  The effects of subtle misinformation in news headlines. , 2014, Journal of experimental psychology. Applied.

[17]  Martin Wattenberg,et al.  The Word Tree, an Interactive Visual Concordance , 2008, IEEE Transactions on Visualization and Computer Graphics.

[18]  Steven Skiena,et al.  Trading Strategies to Exploit Blog and News Sentiment , 2010, ICWSM.

[19]  Serge Fdida,et al.  From popularity prediction to ranking online news , 2014, Social Network Analysis and Mining.

[20]  Michael Karlsson,et al.  Freezing the Flow of Online News : Exploring Approaches to Study the Liquidity of Online News , 2009 .

[21]  ThelwallMike,et al.  Sentiment strength detection in short informal text , 2010 .

[22]  D. Dooling,et al.  Effects of comprehension on retention of prose , 1971 .

[23]  D. L. Hintzman,et al.  First impressions are lasting impressions: A primacy effect in memory for repetitions , 1997 .

[24]  Jürgen Pfeffer,et al.  Characterizing the life cycle of online news stories using social media reactions , 2013, CSCW.

[25]  Fabrício Benevenuto,et al.  Comparing and combining sentiment analysis methods , 2013, COSN '13.

[26]  Mike Thelwall,et al.  Sentiment in short strength detection informal text , 2010 .

[27]  Thomas Gottron,et al.  Bad news travel fast: a content-based analysis of interestingness on Twitter , 2011, WebSci '11.

[28]  Júlio Cesar dos Reis,et al.  Magnet News: You Choose the Polarity of What You Read , 2014, ICWSM.

[29]  David Tewksbury The Seeds of Audience Fragmentation: Specialization in the Use of Online News Sites , 2005 .

[30]  Mor Naaman,et al.  Topicality, time, and sentiment in online news comments , 2011, CHI EA '11.

[31]  Fabrício Benevenuto,et al.  iFeel: a system that compares and combines sentiment analysis methods , 2014, WWW.

[32]  F. McMahon Online News: Journalism and the Internet , 2007 .