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Analyzing Emotional States Induced by News Articles with Latent Semantic Analysis

  • Diana Lupan
  • Mihai Dascălu
  • Ștefan Trăușan-Matu
  • Philippe Dessus
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7557)

Abstract

Emotions are reflected both in verbal and written communication. If in the first case they can be easier to trace due to some specific features (body language, voice tone or inflections), in the second it can be quite tricky to grasp the underlying emotions carried by a written text. Therefore we propose a novel automatic method for analyzing emotions induced by texts, more specifically a reader’s most likely emotional state after reading a news article. In other words, our goal is to determine how reading a piece of news affects a person’s emotional state and to adjust these values based on his/her current state. From a more technical perspective, our system (Emo2Emotions Monitor) combines a context independent approach (actual evaluation of the news employing specific natural language processing techniques and Latent Semantic Analysis) with the influences of user’s present emotional state estimated through his/her specific feedback for building a more accurate image of a person’s emotional state.

Keywords

emotional state Latent Semantic Analysis automatic evaluation of news articles 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Diana Lupan
    • 1
  • Mihai Dascălu
    • 1
    • 2
  • Ștefan Trăușan-Matu
    • 1
  • Philippe Dessus
    • 2
  1. 1.Computer Science DepartmentPolitehnica University of BucharestRomania
  2. 2.LSE, UPMF Grenoble-2 & IUFM-UJF Grenoble-1France

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