Opinion Mining on the Web 2.0 - Characteristics of User Generated Content and Their Impacts

Gerald Petz, Michal Jan Karpowicz, Harald Fürschuß, Andreas Auinger, Václav Stříteský, Andreas Holzinger

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

50 Citations (Scopus)


The field of opinion mining provides a multitude of methods and techniques to be utilized to find, extract and analyze subjective information, such as the one found on social media channels. Because of the differences be-tween these channels as well as their unique characteristics, not all approaches are suitable for each source; there is no “one-size-fits-all” approach. This paper aims at identifying and determining these differences and characteristics by per-forming an empirical analysis as a basis for a discussion which opinion mining approach seems to be applicable to which social media channel.
Original languageEnglish
Title of host publicationHuman-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data - Third International Workshop, HCI-KDD 2013, Held at SouthCHI 2013, Proceedings
Number of pages12
ISBN (Print)978-3-642-39145-3
Publication statusPublished - 2013
EventSouthCHI - Maribor, Slovenia, Slovenia
Duration: 1 Jul 20133 Jul 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7947 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


CityMaribor, Slovenia


  • opinion mining
  • user generated content
  • sentiment analysis
  • text mining
  • content extraction
  • language detection
  • Internet slang


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