Extracting and evaluating conversational patterns in social media: A socio-semantic analysis of customers' reactions to the launch of new products using Twitter streams

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Abstract

In this paper we use Twitter data to assess customers early reactions to the launch of two new products by Apple and Samsung by analyzing the streams generated in a 72 h window around the two events. We present a methodology based on conversational analysis to extract concept maps from Twitter streams and use semantic and topological metrics to compare the conversations. Our findings show that there are significant differences in the structural patterns of the two conversations and that the analysis of these differences can be highly informative about early customers perceptions and value judgments associated with the competing products.

Original languageEnglish
Pages (from-to)490-503
Number of pages14
JournalInternational Journal of Information Management
Volume35
Issue number4
DOIs
StatePublished - 1 Aug 2015

Keywords

  • Actionable intelligence
  • Competitive analysis
  • Competitive intelligence
  • Competitor intelligence
  • Consumer electronics industry
  • Content analysis
  • Social media
  • Text mining
  • Twitter Case study

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