• DocumentCode
    713917
  • Title

    Opinion mining on experience feedback: A case study on smartphones reviews

  • Author

    Brisson, Laurent ; Torrel, Jean-Claude

  • Author_Institution
    Inst. Mines-Telecom, Univ. Eur. de Bretagne, Brest, France
  • fYear
    2015
  • fDate
    13-15 May 2015
  • Firstpage
    187
  • Lastpage
    192
  • Abstract
    Through the development of electronic commerce, social media and collaborative media, the social commerce appeared. Social commerce, a subset of electronic commerce, is based on social interactions in order to buy and sell goods and services. Nowadays, before buying, people give more importance to the experience feedback they found on internet. However, it is difficult to get an overview of this experience feedback since it is scattered in many online resources, and buyers never have time to read many pages of comments. In this paper, we present an approach which grabs and analyzes experience feedback in order to publish a summary of opinions about a product. We develop this approach with a case study on smart phones and publish a dataset of thousands of comments on a wide range of smart phones. To summarize experience feedback, we use a linguistic appraisal model, based on appreciation, affect and judgement, and we set up an approach using methods and tools from the fields of natural language processing, opinion mining and sentiment analysis.
  • Keywords
    Internet; data mining; electronic commerce; groupware; natural language processing; smart phones; social networking (online); Internet; collaborative media; electronic commerce; experience feedback; natural language processing; opinion mining; sentiment analysis; smart phones; social commerce; social media; Appraisal; Automata; Cameras; Knowledge based systems; Pragmatics; Smart phones; Syntactics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Research Challenges in Information Science (RCIS), 2015 IEEE 9th International Conference on
  • Conference_Location
    Athens
  • Type

    conf

  • DOI
    10.1109/RCIS.2015.7128879
  • Filename
    7128879