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Identification of Relevant Hashtags for Planned Events Using Learning to Rank

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Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 976))

Abstract

Lots of planned events (e.g. concerts, sports matches, festivals, etc.) keep happening across the world every day. In various applications like event recommendation, event reporting, etc. it might be useful to find user discussions related to such events from social media. Identification of event related hashtags can be useful for this purpose. In this paper, we focus on identifying the top hashtags related to a given event. We define a set of features for (event, hashtag) pairs, and discuss ways to obtain these feature scores. A linear aggregation of these scores is used to finally output a ranked list of top hashtags for the event. The aggregation weights of the features are obtained using a learning to rank algorithm. We establish the superiority of our method by performing detailed experiments on a large dataset containing multiple categories of events and related tweets.

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Notes

  1. 1.

    https://www.eventbrite.com/.

  2. 2.

    https://eventful.com/.

  3. 3.

    https://www.last.fm/.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Hyderabad, India

    Sreekanth Madisetty & Maunendra Sankar Desarkar

Authors
  1. Sreekanth Madisetty
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  2. Maunendra Sankar Desarkar
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Corresponding author

Correspondence to Sreekanth Madisetty .

Editor information

Editors and Affiliations

  1. Instituto de Telecomunicações, Lisbon, Portugal

    Ana Fred

  2. University of Madeira, Funchal, Portugal

    David Aveiro

  3. Delft University of Technology, Delft, The Netherlands

    Jan L. G. Dietz

  4. Henley Business School, University of Reading, Reading, UK

    Kecheng Liu

  5. University of Coimbra, Coimbra, Portugal

    Jorge Bernardino

  6. Federal University of Pernambuco, Recife, Brazil

    Ana Salgado

  7. INSTICC and Instituto Politecnico de Setúbal, Setúbal, Portugal

    Joaquim Filipe

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Madisetty, S., Desarkar, M.S. (2019). Identification of Relevant Hashtags for Planned Events Using Learning to Rank. In: Fred, A., et al. Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2017. Communications in Computer and Information Science, vol 976. Springer, Cham. https://doi.org/10.1007/978-3-030-15640-4_5

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  • DOI: https://doi.org/10.1007/978-3-030-15640-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15639-8

  • Online ISBN: 978-3-030-15640-4

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