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Psychological relevance and information science

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  • Stephen P. Harter

Abstract

This article summarizes the theory of psychological relevance proposed by Dan Sperber and Deirdre Wilson (1986), to explicate the relevance of speech utterances to hearers in everyday conversation. The theory is then interpreted as the concept of relevance in information retrieval, and an extended example is presented. Implications of psychological relevance for research in information retrieval; evaluation of information retrieval systems; and the concepts of information, information need, and the information‐seeking process are explored. Connections of the theory to ideas in bibliometrics are also suggested. © 1992 John Wiley & Sons, Inc.

Suggested Citation

  • Stephen P. Harter, 1992. "Psychological relevance and information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 602-615, October.
    • Handle: RePEc:bla:jamest:v:43:y:1992:i:9:p:602-615
    DOI: 10.1002/(SICI)1097-4571(199210)43:93.0.CO;2-Q
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    Cited by:

    1. Zhang, Lei & Kopak, Rick & Freund, Luanne & Rasmussen, Edie, 2011. "Making functional units functional: The role of rhetorical structure in use of scholarly journal articles," International Journal of Information Management, Elsevier, vol. 31(1), pages 21-29.
    2. Wayne de Fremery & Michael K. Buckland, 2022. "Context, relevance, and labor," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(9), pages 1268-1278, September.
    3. Jensen, Scott & Liu, Xiaozhong & Yu, Yingying & Milojevic, Staša, 2016. "Generation of topic evolution trees from heterogeneous bibliographic networks," Journal of Informetrics, Elsevier, vol. 10(2), pages 606-621.
    4. Ian Ruthven, 2021. "Resonance and the experience of relevance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(5), pages 554-569, May.
    5. Antonio Maria Rinaldi & Cristiano Russo & Cristian Tommasino, 2020. "A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features," Future Internet, MDPI, vol. 12(11), pages 1-20, October.
    6. Howard D. White, 2010. "Some new tests of relevance theory in information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 653-667, June.
    7. Howard D. White, 2018. "Pennants for Garfield: bibliometrics and document retrieval," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 757-778, February.
    8. Xiaoli Huang & Dagobert Soergel, 2013. "Relevance: An improved framework for explicating the notion," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 18-35, January.
    9. Marcia J. Bates, 2011. "Birger Hjørland's Manichean misconstruction of Marcia Bates' work," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 2038-2044, October.
    10. Min Sook Park & JungHo Park & Hyejin Kim & Jin Hui Lee & Hyejin Park, 2023. "Measuring the impacts of quantity and trustworthiness of information on COVID‐19 vaccination intent," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(7), pages 846-865, July.
    11. Nathalie Demoulin & Kristof Coussement, 2018. "Acceptance of text-mining systems: The signaling role of information quality," Post-Print hal-02111772, HAL.
    12. Howard D. White, 2015. "Co-cited author retrieval and relevance theory: examples from the humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2275-2299, March.
    13. Rekha P. Upadhye & V. L. Kalyane & Vijai Kumar & E. R. Prakasan, 2004. "Scientometric analysis of synchronous references in the Physics Nobel lectures, 1981-1985: A pilot study," Scientometrics, Springer;Akadémiai Kiadó, vol. 61(1), pages 55-68, September.
    14. Pin Li & Guoli Yang & Chuanqi Wang, 2019. "Visual topical analysis of library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1753-1791, December.

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