Towards automatic assessment of the social media impact of news content

Tom De Nies, Gerald Haesendonck, Fréderic Godin, Wesley De Neve, Erik Mannens, Rik Van de Walle

Abstract: In this paper, we investigate the possibilities to estimate the impact the content of a news article has on social media, and in particular on Twitter. We propose an approach that makes use of captured and temporarily stored microposts found in social media, and compares their relevance to an arbitrary news article. These results are used to derive key indicators of the social media impact of the specified content. We describe each step of our approach, provide a first implementation, and discuss the most imminent challenges and discussion points.