Extracting and evaluating conversational patterns in social media: A socio-semantic analysis of customers’ reactions to the launch of new products using Twitter streams
作者：
Highlights：
• Reactions to new products by Apple and Samsung are assessed analyzing Twitter streams.
• Streams are modeled as virtual conversations, generating dynamically updated concept maps.
• Using topological analysis we identify patterns of what people say and how they talk.
• Apple conversation is less fragmented, contains more topics, and less negative sentiment.
摘要
•Reactions to new products by Apple and Samsung are assessed analyzing Twitter streams.•Streams are modeled as virtual conversations, generating dynamically updated concept maps.•Using topological analysis we identify patterns of what people say and how they talk.•Apple conversation is less fragmented, contains more topics, and less negative sentiment.
论文关键词：Social media,Twitter Case study,Consumer electronics industry,Competitive analysis,Competitive intelligence,Competitor intelligence,Actionable intelligence,Text mining,Content analysis
论文评审过程：Received 3 October 2014, Revised 2 April 2015, Accepted 3 April 2015, Available online 13 May 2015.
论文官网地址：https://doi.org/10.1016/j.ijinfomgt.2015.04.001
