A path-based model for emotion abstraction on facebook using sentiment analysis and taxonomy knowledge

Valentina Franzoni, Yuanxi Li, Paolo Mengoni

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

19 Citations (Scopus)

Abstract

Each term in a short text can potentially convey emotional meaning. Facebook comments and shared posts often convey human biases, which play a pivotal role in information spreading and content consumption. Such bias is at the basis of humangenerated content, and capable of conveying contexts which shape the opinion of users through the social media flow of information. Starting from the observation that a separation in topic clusters, i.e. sub-contexts, spontaneously occur if evaluated by human common sense, this work introduces a process for automated extraction of sub-context in Facebook. Basing on emotional abstraction and valence, the automated extraction is exploited through a class of path-based semantic similarity measures and sentiment analysis. Experimental results are obtained using validated clustering techniques on such features, on the domain of information security, over a sample of over 9 million page users. An additional expert evaluation of clusters in tag clouds confirms that the proposed automated algorithm for emotional abstraction clusters Facebook comments compatibly with human common sense. The baseline methods rely on the robust notion of collective concept similarity.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Web Intelligence 2017
PublisherAssociation for Computing Machinery, Inc
Pages947-952
Number of pages6
ISBN (Electronic)9781450349512
DOIs
Publication statusPublished - 23 Aug 2017
Event16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017 - Leipzig, Germany
Duration: 23 Aug 201726 Aug 2017

Publication series

NameProceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017

Conference

Conference16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017
Country/TerritoryGermany
CityLeipzig
Period23/08/1726/08/17

Scopus Subject Areas

  • Computer Networks and Communications
  • Artificial Intelligence
  • Software

User-Defined Keywords

  • Artificial intelligence
  • Collective knowledge
  • Data mining
  • Emotional abstraction
  • Knowledge discovery
  • Semantic distance
  • Sentiment analysis
  • Word similarity

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