User Mood Tracking for Opinion Analysis on Twitter

  • Giuseppe CastellucciEmail author
  • Danilo Croce
  • Diego De Cao
  • Roberto Basili
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10037)


The huge variability of trends, community interests and jargon is a crucial challenge for the application of language technologies to Social Media analysis. Models, such as grammars and lexicons, are exposed to rapid obsolescence, due to the speed at which topics as well as slogans change during time. In Sentiment Analysis, several works dynamically acquire the so-called opinionated lexicons. These are dictionaries where information regarding subjectivity aspects of individual words are described. This paper proposes an architecture for dynamic sentiment analysis over Twitter, combining structured learning and lexicon acquisition. Evidence about the beneficial effects of a dynamic architecture is reported through large scale tests over Twitter streams in Italian.


Social media analytics Sentiment analysis Opinion mining Polarity lexicons 


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Giuseppe Castellucci
    • 1
    Email author
  • Danilo Croce
    • 2
  • Diego De Cao
    • 1
  • Roberto Basili
    • 2
  1. 1.Reveal s.r.l.RomeItaly
  2. 2.Department of Enterprise EngineeringUniversity of Roma Tor VergataRomeItaly

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