Characterizing the life cycle of online news stories using social media reactions

• DOI: 10.1145/2531602.2531623
• Publication Date: 2014-02-07T14:23:08Z
• Authors: Carlos Castillo; Mohammed El-Haddad; Jürgen Pfeffer; Matt Stempeck
• Keywords: Qualitative analysis; Data set

This paper presents a study of the life cycle news articles posted online. We describe interplay between website visitation patterns and social media reactions to content. show that we can use this hybrid observation method characterize distinct classes articles. also find help predict future early accurately. validate our methods using qualitative analysis as well quantitative on data from large international network, for set generating more than 3,000,000 visits 200,000 reactions. it is possible model accurately overall traffic will ultimately receive by observing first ten twenty minutes Achieving same prediction accuracy with alone would require wait three hours data. significant improvements shelf-life stories.