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Wiki-MID: A Very Large Multi-domain Interests Dataset of Twitter Users with Mappings to Wikipedia

  • Giorgia Di Tommaso
  • Stefano Faralli
  • Giovanni StiloEmail author
  • Paola Velardi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11137)

Abstract

This paper presents Wiki-MID, a LOD compliant multi-domain interests dataset to train and test Recommender Systems, and the methodology to create the dataset from Twitter messages in English and Italian. Our English dataset includes an average of 90 multi-domain preferences per user on music, books, movies, celebrities, sport, politics and much more, for about half million users traced during six months in 2017. Preferences are either extracted from messages of users who use Spotify, Goodreads and other similar content sharing platforms, or induced from their “topical” friends, i.e., followees representing an interest rather than a social relation between peers. In addition, preferred items are matched with Wikipedia articles describing them. This unique feature of our dataset provides a mean to categorize preferred items, exploiting available semantic resources linked to Wikipedia such as the Wikipedia Category Graph, DBpedia, BabelNet and others.

Keywords

Semantic recommenders Twitter Wikipedia Users’ interest 

Notes

Acknowledgments

This work has been supported by the IBM Faculty Award #2305895190 and by the MIUR under grant “Dipartimenti di eccellenza 2018–2022” of the Department of Computer Science of Sapienza University.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Giorgia Di Tommaso
    • 1
  • Stefano Faralli
    • 2
  • Giovanni Stilo
    • 1
    Email author
  • Paola Velardi
    • 1
  1. 1.Department of Computer ScienceUniversity La Sapienza of RomeRomeItaly
  2. 2.Unitelma-SapienzaRomeItaly

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