• DocumentCode
    116552
  • Title

    Accelerate the detection of trends by using sentiment analysis within the blogosphere

  • Author

    Hennig, Philipp ; Berger, P. ; Lehmann, Craig ; Mascher, Andrina ; Meinel, Christoph

  • Author_Institution
    Hasso-Plattner-Inst., Univ. of Potsdam, Potsdam, Germany
  • fYear
    2014
  • fDate
    17-20 Aug. 2014
  • Firstpage
    503
  • Lastpage
    508
  • Abstract
    Information about upcoming trends is considered to be a valuable source of knowledge for both, companies and individuals. A large number of market analysts working at monitoring a particular business field, with many employing manual methods to do so. Since the amount of available data on the internet is far too high for humans to monitor, which carries a major risk of substantial amount of information being missed, the necessity arose to detect emerging trends automatically. Weblogs are an important medium to publish information and discuss certain topics. The web platform BlogIntelligence analyzes and visualizes the content and interconnection of blogs in the blogosphere. One area of focus is the detection of trends over a period of time, which is especially helpful for product vendors. But even more interesting, views expressed in weblog posts influence the reader´s opinion. Integrating the strength and direction of expressed sentiments enhances the trend detection significantly. In this work, we introduce an approach to enrich the trend detection with sentiment analysis.
  • Keywords
    Internet; Web sites; data mining; BlogIntelligence Web platform; Internet; Weblogs; blogosphere; business field; market analysts; product vendors; sentiment analysis; trend detection; Blogs; Conferences; Data visualization; Market research; Sentiment analysis; Social network services; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/ASONAM.2014.6921633
  • Filename
    6921633