How did the popularity of the Greek Prime Minister evolve in 2015? How did the predominant sentiment about him vary during that period? Were there any controversial sub-periods? What other entities were related to him during these periods? To answer these questions, one needs to analyze archived documents and data about the query entities, such as old news articles or social media archives. In particular, user-generated content posted in social networks, like Twitter and Facebook, can be seen as a comprehensive documentation of our society, and thus, meaningful analysis methods over such archived data are of immense value for sociologists, historians, and other interested parties who want to study the history and evolution of entities and events. To this end, in this paper we propose an entity-centric approach to analyze social media archives and we define measures that allow studying how entities were reflected in social media in different time periods and under different aspects, like popularity, attitude, controversiality, and connectedness with other entities. A case study using a large Twitter archive of 4 years illustrates the insights that can be gained by such an entity-centric and multi-aspect analysis.

中文翻译：

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追踪实体的历史和演变：大型社交媒体档案的以实体为中心的时间分析

2015年希腊总理的知名度如何演变？在此期间，关于他的主要情绪有何变化？有争议的子时段吗？在这些期间，其他哪些实体与他有关？为了回答这些问题，需要分析有关查询实体的存档文档和数据，例如旧新闻文章或社交媒体档案。特别是，在Twitter和Facebook等社交网络上发布的用户生成的内容可以看作是我们社会的全面文档，因此，对此类存档数据进行有意义的分析方法对于社会学家，历史学家和其他感兴趣的人来说具有巨大的价值。想要研究实体和事件的历史和演变的团体。为此，在本文中，我们提出了一种以实体为中心的方法来分析社交媒体档案，并且我们定义了一些措施，以研究实体如何在不同时间段和不同方面（如受欢迎程度，态度，争议性以及与其他实体的联系）在社交媒体中得到反映。 。案例研究使用了一个大型Twitter档案（历时4年），说明了通过这种以实体为中心和多方面的分析可以获得的见解。