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Social Search and Task-Related Relevance Dimensions in Microblogging Sites

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Social Informatics (SocInfo 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12467))

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Abstract

Social media, and in particular microblogging sites, allow users to post multiple kinds of content for different purposes. Content may be purely conversational, or news-related, or event-related. To find information relevant to users in this heterogeneous mass of content, it would be important to consider the task for which search is carried out, and the most suitable relevance dimensions. In the last years, despite the social search problem has been increasingly investigated, this aspect has not been sufficiently analyzed. For this reason, in this paper, we focus on different search tasks in the microblog search context, and we identify some related relevance dimensions. We also report some experiments we have made to verify the impact of the identified relevance dimensions on the system effectiveness, with respect to the considered search tasks.

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Notes

  1. 1.

    https://www.statista.com/statistics/282087/number-of-monthly-active-twitter-users/.

  2. 2.

    https://www.journalism.org/2017/09/07/news-use-across-social-media-platforms-2017/.

  3. 3.

    https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html.

  4. 4.

    In this case, being a related tweet means that the tweet discusses the crisis event.

  5. 5.

    Also for informativeness, logistic regression has been performed by employing the model implemented by the scikit-learn library [36], using the default parameters.

  6. 6.

    https://radimrehurek.com/gensim/models/ldamodel.html.

  7. 7.

    https://www.computing.dcu.ie/~dganguly/smerp2017/.

  8. 8.

    https://lucene.apache.org/.

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Author information

Authors and Affiliations

  1. Department of Informatics, Systems, and Communication (DISCo), Information and Knowledge Repersentation, Retrieval, and Reasoning (IKR3) Lab, University of Milano-Bicocca, Edificio U14, Viale Sarca 336, 20126, Milan, Italy

    Divi Galih Prasetyo Putri, Marco Viviani & Gabriella Pasi

Authors
  1. Divi Galih Prasetyo Putri
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  2. Marco Viviani
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  3. Gabriella Pasi
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Corresponding author

Correspondence to Marco Viviani .

Editor information

Editors and Affiliations

  1. Max Planck Institute for Demographic Research, Rostock, Germany

    Samin Aref

  2. University of Sheffield, Sheffield, UK

    Kalina Bontcheva

  3. King’s College London, London, UK

    Marco Braghieri

  4. Umeå University, Umeå, Sweden

    Frank Dignum

  5. ISTI-CNR, Pisa, Italy

    Fosca Giannotti

  6. University of Pisa, Pisa, Italy

    Francesco Grisolia

  7. University of Pisa, Pisa, Italy

    Dino Pedreschi

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Putri, D.G.P., Viviani, M., Pasi, G. (2020). Social Search and Task-Related Relevance Dimensions in Microblogging Sites. In: Aref, S., et al. Social Informatics. SocInfo 2020. Lecture Notes in Computer Science(), vol 12467. Springer, Cham. https://doi.org/10.1007/978-3-030-60975-7_22

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  • DOI: https://doi.org/10.1007/978-3-030-60975-7_22

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