The impact of time in link-based Web ranking

• Type: Article in International Scientific Journal
• Date: 2013

Authors

Sérgio Nunes (Author) FEUP; Cristina Ribeiro (Author) FEUP; Gabriel David (Author) FEUP

Journal

Title: Information Research

Vol. 18

ISSN: 1368-1613

Publisher: University of Boras

Indexing

ISI Web of Knowledge - 3 Citations

ISI Web of Science

Scopus - 2 Citations

INSPEC

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Humanities > Information science > Information management > Information processing

Other information

Authenticus ID: P-008-ECV

Abstract (EN): Introduction. The strong dynamic nature of the Web is a well-known reality. Nonetheless, research on Web dynamics is still a minor part of mainstream Web research. This is largely the case in Web link analysis. In this paper we investigate and measure the impact of time in link-based ranking algorithms on a particular subset of the Web, specifically blogs. Method. Using a large collection of blog posts that span more than three years, we compare a traditional link-based ranking algorithm with a time-biased alternative, providing some insights into the evolution of link data over time. We designed two experiments to evaluate the use of temporal features in authority estimation algorithms. In the first experiment we compare time-independent and time-sensitive ranking algorithms with a reference rank based on the total number of visits to each blog. In the second, we use feedback from communication media domain experts to contrast different rankings of Portuguese news Websites. Results. The distribution of citations to a Web document over time contains valuable information. Based on several examples we show that time-independent algorithms are unable to capture the correct popularity of sites with high citation activity. Using a reference rank based on the number of visits to a site, we show that a time-biased approach has a better performance. Conclusions. Although both time-independent and time-aware approaches are based on the same raw data, the experiments indicate that they can be treated as complementary signals for relevance assessment by information retrieval systems. We show that temporal information present in blogs can be used to derive stable time-dependent features, which can be successfully used in the context of Web document ranking.

Language: English

Type (Professor's evaluation): Scientific

Notes: Available at http://InformationR.net/ir/18-3/paper586.html

No. of pages: 12