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Finding and tracking subjects within an ongoing debate

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  • Prabowo, Rudy
  • Thelwall, Mike

Abstract

This paper describes a new algorithm for finding and tracking different subjects within an ongoing debate. The algorithm finds blocks of co-occurring terms, representing subjects, including blocks for which the term co-occurrence pattern forms a ring topology. We used short online debate forum data and longer summary bulletins to assess the extent to which the algorithm could correctly detect subjects, according to the judgements of human evaluators. The results show that it could normally detect subject-shifting and track different subjects over time in online debate forums and with adjustments could find subjects in bulletins, but could not track the subjects in the bulletins because the interlinking between subjects was too dense in the longer documents.

Suggested Citation

  • Prabowo, Rudy & Thelwall, Mike, 2008. "Finding and tracking subjects within an ongoing debate," Journal of Informetrics, Elsevier, vol. 2(2), pages 107-127.
    • Handle: RePEc:eee:infome:v:2:y:2008:i:2:p:107-127
    DOI: 10.1016/j.joi.2007.12.002
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    References listed on IDEAS

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    1. Mike Thelwall & Rudy Prabowo & Ruth Fairclough, 2006. "Are raw RSS feeds suitable for broad issue scanning? A science concern case study," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(12), pages 1644-1654, October.
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    Cited by:

    1. Vasileiadou, Eleftheria, 2009. "Stabilisation operationalised: Using time series analysis to understand the dynamics of research collaboration," Journal of Informetrics, Elsevier, vol. 3(1), pages 36-48.

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    More about this item

    Keywords

    Feature selection; Subject tracking;

    Statistics

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