Trend detection through temporal link analysis

  • Authors:

  • Einat Amitay;David Carmel;Michael Herscovici;Ronny Lempel;Aya Soffer

  • Affiliations:

  • IBM Research Lab in Haifa, Haifa 31905, Israel;IBM Research Lab in Haifa, Haifa 31905, Israel;IBM Research Lab in Haifa, Haifa 31905, Israel;IBM Research Lab in Haifa, Haifa 31905, Israel;IBM Research Lab in Haifa, Haifa 31905, Israel

  • Venue:
  • Journal of the American Society for Information Science and Technology - Special issue: Webometrics
  • Year:
  • 2004

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Abstract

Although time has been recognized as an important dimension in the co-citation literature, to date it has not been incorporated into the analogous process of link analysis on the Web. In this paper, we discuss several aspects and uses of the time dimension in the context of Web information retrieval. We describe the ideal case-- where search engines track and store temporal data for each of the pages in their repository, assigning timestamps to the hyperlinks embedded within the pages. We introduce several applications which benefit from the availability of such timestamps. To demonstrate our claims, we use a somewhat simplistic approach, which dates links by approximating the age of the page's content. We show that by using this crude measure alone it is possible to detect and expose significant events and trends. We predict that by using more robust methods for tracking modifications in the content of pages, search engines will be able to provide results that are more timely and better reflect current real-life trends than those they provide today.