Auditing Source Diversity Bias in Video Search Results Using Virtual Agents
Abstract: We audit the presence of domain-level source diversity bias in video search results. Using a virtual agent-based approach, we compare outputs of four Western and one non-Western search engines for English and Russian queries. Our findings highlight that source diversity varies substantially depending on the language with English queries returning more diverse outputs. We also find disproportionately high presence of a single platform, YouTube, in top search outputs for all Western search engines except Google. At the same time, we observe that Youtube’s major competitors such as Vimeo or Dailymotion do not appear in the sampled Google’s video search results. This finding suggests that Google might be downgrading the results from the main competitors of Google-owned Youtube and highlights the necessity for further studies focusing on the presence of own-content bias in Google’s search results
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource, 232-236 S.
- Sprache
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Englisch
- Anmerkungen
-
Veröffentlichungsversion
begutachtet (peer reviewed)
In: Leskovec, Jure (Hg.), Grobelnik, Marko (Hg.), Najork, Marc (Hg.), Tang, Jie (Hg.), Zia, Leila (Hg.): WWW '21: Companion Proceedings of the Web Conference 2021. 2021. S. 232-236. ISBN 978-1-4503-8313-4
- Ereignis
-
Veröffentlichung
- (wo)
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Mannheim
- (wer)
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SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
- (wann)
-
2021
- Ereignis
-
Veröffentlichung
- (wo)
-
New York
- (wer)
-
Association for Computing Machinery
- (wann)
-
2021
- Urheber
- Beteiligte Personen und Organisationen
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Leskovec, Jure
Grobelnik, Marko
Najork, Marc
Tang, Jie
Zia, Leila
- DOI
-
10.1145/3442442.3452306
- URN
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urn:nbn:de:0168-ssoar-75365-2
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 05:24 UTC
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Beteiligte
- Urman, Aleksandra
- Makhortykh, Mykola
- Ulloa, Roberto
- Leskovec, Jure
- Grobelnik, Marko
- Najork, Marc
- Tang, Jie
- Zia, Leila
- SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
- Association for Computing Machinery
Entstanden
- 2021
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