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How did the popularity of the Greek Prime Minister evolve in 2015? How didthe predominant sentiment about him vary during that period? Were there anycontroversial sub-periods? What other entities were related to him during theseperiods? To answer these questions, one needs to analyze archived documents anddata about the query entities, such as old news articles or social mediaarchives. In particular, user-generated content posted in social networks, likeTwitter and Facebook, can be seen as a comprehensive documentation of oursociety, and thus meaningful analysis methods over such archived data are ofimmense value for sociologists, historians and other interested parties whowant to study the history and evolution of entities and events. To this end, inthis paper we propose an entity-centric approach to analyze social mediaarchives and we define measures that allow studying how entities were reflectedin social media in different time periods and under different aspects, likepopularity, attitude, controversiality, and connectedness with other entities.A case study using a large Twitter archive of four years illustrates theinsights that can be gained by such an entity-centric and multi-aspectanalysis.

Tracking the History and Evolution of Entities: Entity-centric Temporal Analysis of Large Social Media Archives