Now showing items 1-6 of 6

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      Harmony and dissonance: organizing the people's voices on political controversies

      Awadallah, Rawia; Ramanath, Maya; Weikum, Gerhard (ACM, 2012)
      The wikileaks documents about the death of Osama Bin Laden and the debates about the economic crisis in Greece and other European countries are some of the controversial topics being played on the news everyday. Each of ...
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      Language-model-based pro/con classification of political text

      Awadallah, Rawia; Ramanath, Maya; Weikum, Gerhard (ACM, 2010)
      Given a controversial political topic, our aim is to classify documents debating the topic into pro or con. Our approach extracts topic related terms, pro/con related terms, and pairs of topic related and pro/con related ...
    • OpinioNetIt: A structured and faceted knowledge-base of opinions

      Awadallah, Rawia; Ramanath, Maya; Weikum, Gerhard (IEEE, 2012)
      We propose a demonstration of our system, OpinioNetIt, a structured, faceted, knowledge-base of opinions, and its use in political analysis. OpinioNetIt consists of information about people, topics and opinions in the form ...
    • OpinioNetIt: Understanding the Opinions-People network for politically controversial topics

      Awadallah, Rawia; Ramanath, Maya; Weikum, Gerhard (ACM, 2011)
      The wikileaks documents or the economic crises in Ireland and Portugal are some of the controversial topics being played on the news everyday. Each of these topics has many different aspects, and there is no absolute, ...
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      Opinions network for politically controversial topics

      Awadallah, Rawia; Ramanath, Maya; Weikum, Gerhard (ACM, 2012)
      This paper describes OpinioNetIt, a structured, faceted, knowledge-base of opinions, and its use in political opinions analysis. OpinioNetIt consists of information about people, topics and opinions in the form of person, ...
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      PolariCQ: Polarity classification of political quotations

      Awadallah, Rawia; Ramanath, Maya; Weikum, Gerhard (ACM, 2012)
      We consider the problem of automatically classifying quotations about political debates into both topic and polarity. These quotations typically appear in news media and online forums. Our approach maps quotations onto one ...