One world, one opinion? The superstar effect in LLM responses

Sofie Goethals; Lauren Rhue

doi:10.18653/v1/2025.c3nlp-1.8

One world, one opinion? The superstar effect in LLM responses

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Abstract

As large language models (LLMs) are shaping the way information is shared and accessed online, their opinions have the potential to influence a wide audience. This study examines who is predicted by the studied LLMs as the most prominent figures across various fields, while using prompts in ten different languages to explore the influence of linguistic diversity. Our findings reveal low diversity in responses, with a small number of figures dominating recognition across languages (also known as the “superstar effect”). These results highlight the risk of narrowing global knowledge representation when LLMs are used to retrieve subjective information.

Anthology ID:: 2025.c3nlp-1.8
Volume:: Proceedings of the 3rd Workshop on Cross-Cultural Considerations in NLP (C3NLP 2025)
Month:: May
Year:: 2025
Address:: Albuquerque, New Mexico
Editors:: Vinodkumar Prabhakaran, Sunipa Dev, Luciana Benotti, Daniel Hershcovich, Yong Cao, Li Zhou, Laura Cabello, Ife Adebara
Venues:: C3NLP | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 89–107
Language:
URL:: https://aclanthology.org/2025.c3nlp-1.8/
DOI:: 10.18653/v1/2025.c3nlp-1.8
Bibkey:
Cite (ACL):: Sofie Goethals and Lauren Rhue. 2025. One world, one opinion? The superstar effect in LLM responses. In Proceedings of the 3rd Workshop on Cross-Cultural Considerations in NLP (C3NLP 2025), pages 89–107, Albuquerque, New Mexico. Association for Computational Linguistics.
Cite (Informal):: One world, one opinion? The superstar effect in LLM responses (Goethals & Rhue, C3NLP 2025)
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PDF:: https://aclanthology.org/2025.c3nlp-1.8.pdf

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@inproceedings{goethals-rhue-2025-one,
    title = "One world, one opinion? The superstar effect in {LLM} responses",
    author = "Goethals, Sofie  and
      Rhue, Lauren",
    editor = "Prabhakaran, Vinodkumar  and
      Dev, Sunipa  and
      Benotti, Luciana  and
      Hershcovich, Daniel  and
      Cao, Yong  and
      Zhou, Li  and
      Cabello, Laura  and
      Adebara, Ife",
    booktitle = "Proceedings of the 3rd Workshop on Cross-Cultural Considerations in NLP (C3NLP 2025)",
    month = may,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.c3nlp-1.8/",
    doi = "10.18653/v1/2025.c3nlp-1.8",
    pages = "89--107",
    ISBN = "979-8-89176-237-4",
    abstract = "As large language models (LLMs) are shaping the way information is shared and accessed online, their opinions have the potential to influence a wide audience. This study examines who is predicted by the studied LLMs as the most prominent figures across various fields, while using prompts in ten different languages to explore the influence of linguistic diversity. Our findings reveal low diversity in responses, with a small number of figures dominating recognition across languages (also known as the ``superstar effect''). These results highlight the risk of narrowing global knowledge representation when LLMs are used to retrieve subjective information."
}

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%0 Conference Proceedings
%T One world, one opinion? The superstar effect in LLM responses
%A Goethals, Sofie
%A Rhue, Lauren
%Y Prabhakaran, Vinodkumar
%Y Dev, Sunipa
%Y Benotti, Luciana
%Y Hershcovich, Daniel
%Y Cao, Yong
%Y Zhou, Li
%Y Cabello, Laura
%Y Adebara, Ife
%S Proceedings of the 3rd Workshop on Cross-Cultural Considerations in NLP (C3NLP 2025)
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-237-4
%F goethals-rhue-2025-one
%X As large language models (LLMs) are shaping the way information is shared and accessed online, their opinions have the potential to influence a wide audience. This study examines who is predicted by the studied LLMs as the most prominent figures across various fields, while using prompts in ten different languages to explore the influence of linguistic diversity. Our findings reveal low diversity in responses, with a small number of figures dominating recognition across languages (also known as the “superstar effect”). These results highlight the risk of narrowing global knowledge representation when LLMs are used to retrieve subjective information.
%R 10.18653/v1/2025.c3nlp-1.8
%U https://aclanthology.org/2025.c3nlp-1.8/
%U https://doi.org/10.18653/v1/2025.c3nlp-1.8
%P 89-107

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Markdown (Informal)

[One world, one opinion? The superstar effect in LLM responses](https://aclanthology.org/2025.c3nlp-1.8/) (Goethals & Rhue, C3NLP 2025)

One world, one opinion? The superstar effect in LLM responses (Goethals & Rhue, C3NLP 2025)

ACL

Sofie Goethals and Lauren Rhue. 2025. One world, one opinion? The superstar effect in LLM responses. In Proceedings of the 3rd Workshop on Cross-Cultural Considerations in NLP (C3NLP 2025), pages 89–107, Albuquerque, New Mexico. Association for Computational Linguistics.