Prof. Dr. Felix Naumann

Konstantina Lazaridou

Hasso-Plattner-Institut für Softwaresystemtechnik

Address: Prof.-Dr.-Helmert-Straße 2-3, D-14482 Potsdam
Phone: +49 331 5509 292
Room: Campus III G-3.2.08
Email:  konstantina.lazaridou(at)hpi.de


Ph.D. candidate at the Infomation Systems Research Group and member of the Web Science Group at the Hasso Plattner Institute for Software Systems Engineering.


Research Interests

  • Data mining & Machine Learning
  • Information Retrieval
  • News and Social Media Analysis
  • Opinion and Sentiment Analysis
  • Web Mining
  • Graph Mining


  • Information Retrieval and Web Search (Lecture, WS 2015/2016)
  • Graph Mining (Lecture, WS 2016/2017)
  • Recommender Systems (Seminar, SS 2017)
  • Text Mining (Seminar, SS 2017)


Master theses

  • Classification of German Newspaper Comments by Godde Christian, 2016
  • Large-scale Topic-based Analysis of Political Discussions on Twitter, Jaqueline Pollak, 2017


Identifying Political Bias in News Articles

in . volume   12   of   Bulletin 12 , IEEE Technical Committee on Digital Libraries , TPDL Doctoral Consortium 2016 .

Individuals' political leaning, such as journalists', politicians' etc. often shapes the public opinion over several issues. In the case of online journalism, due to the numerous ongoing events, newspapers have to choose which stories to cover, emphasize on and possibly express their opinion about. These choices depict their profile and could reveal a potential bias towards a certain perspective or political position. Likewise, politicians' choice of language and the issues they broach are an indication of their beliefs and political orientation. Given the amount of user-generated text content online, such as news articles, blog posts, politician statements etc., automatically analyzing this information becomes increasingly interesting, in order to understand what people stand for and how they influence the general public. In this PhD thesis, we analyze UK news corpora along with parliament speeches in order to identify potential political media bias. We currently examine the politicians' mentions and their quotes in news articles and how this referencing pattern evolves in time.
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Further Information
Tags isg media_bias news_analysis web_science