research-article

Competitive Search

Authors:

Moshe TennenholtzAuthors Info & Claims

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 2838 - 2849

https://doi.org/10.1145/3477495.3532771

Published: 07 July 2022 Publication History

Abstract

The Web is a canonical example of a competitive search setting that includes document authors with ranking incentives: their goal is to promote their documents in rankings induced for queries. The incentives affect some of the corpus dynamics as the authors respond to rankings by applying strategic document manipulations. This well known reality has deep consequences that go well beyond the need to fight spam. As a case in point, researchers showed using game theoretic analysis that the probability ranking principle is not optimal in competitive retrieval settings; specifically, it leads to reduced topical diversity in the corpus. We provide a broad perspective on recent work on competitive retrieval settings, argue that this work is the tip of the iceberg, and pose a suite of novel research directions; for example, a general game theoretic framework for competitive search, methods of learning-to-rank that account for post-ranking effects, approaches to automatic document manipulation, addressing societal aspects and evaluation.

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Frew LNelson MWeigle MSerra ESpezzano F(2024)Retrogressive Document Manipulation of US Federal Environmental WebsitesProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679988(3762-3766)Online publication date: 21-Oct-2024
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Index Terms

Competitive Search
1. Information systems
  1. Information retrieval
    1. Search engine architectures and scalability
      1. Adversarial retrieval

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cover image ACM Conferences

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2022

3569 pages

ISBN:9781450387323

DOI:10.1145/3477495

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UAM and Amazon
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Julio Gonzalo
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J. Shane Culpepper
RMIT University
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Gabriella Kazai
Waseda University

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Frew LNelson MWeigle MSerra ESpezzano F(2024)Retrogressive Document Manipulation of US Federal Environmental WebsitesProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679988(3762-3766)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679988
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