An Analysis of Social Data Credibility for Services Systems in Smart Cities – Credibility Assessment and Classification of Tweets

  • Iman Abu Hashish
  • Gianmario Motta
  • Tianyi Ma
  • Kaixu Liu
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 189)


In the “Information Age”, Smart Cities rely on a wide range of different data sources. Among them, social networks can play a big role, if information veracity is assessed. Veracity assessment has been, and is, a rather popular research field. Specifically, our work investigates the credibility of data from Twitter, an online social network and a news media, by considering not only credibility, and type, but also origin. Our analysis proceeds in four phases: Features Extraction, Features Analysis, Features Selection, and Classification. Finally, we classify whether a Tweet is credible or incredible, is rumor or spam, is generated by a human or a Bot. We use Social Media Mining and Machine Learning techniques. Our analysis reaches an overall accuracy higher than the benchmark, and it adds the origin dimension to the credibility analysis method.


Smart cities Smart citizens Social data Twitter Twitter bot Credibility Veracity Classification Social media mining Machine learning 


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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Iman Abu Hashish
    • 1
  • Gianmario Motta
    • 1
  • Tianyi Ma
    • 1
  • Kaixu Liu
    • 1
  1. 1.Department of Electronics, Computer Science and Electrical EngineeringUniversity of PaviaPaviaItaly

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