Social media conversation monitoring: Visualize information contents of twitter messages using conversational metrics

Carlo Lipizzi, Dante Gama Dessavre, Luca Iandoli, José Emmanuel Ramirez Marquez

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

In this paper we present a novel method to extract and visualize actionable information from streams of social media messages, analyzed as conversational elements. Our method has been applied to over 4 million messages related to more than 35 different events, demonstrating good results identifying conversational patterns.

Original languageEnglish
Pages (from-to)2216-2220
Number of pages5
JournalProcedia Computer Science
Volume80
DOIs
StatePublished - 2016
EventInternational Conference on Computational Science, ICCS 2016 - San Diego, United States
Duration: 6 Jun 20168 Jun 2016

Keywords

  • Content analysis
  • Conversation analysis
  • Social media
  • Text mining
  • Visualization

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