Algorithmic amplification of biases on Google Search
- URL: http://arxiv.org/abs/2401.09044v1
- Date: Wed, 17 Jan 2024 08:24:57 GMT
- Title: Algorithmic amplification of biases on Google Search
- Authors: Hussam Habib, Ryan Stoldt, Andrew High, Brian Ekdale, Ashley Peterson,
Katy Biddle, Javie Ssozi, and Rishab Nithyanand
- Abstract summary: This paper investigates how individuals' preexisting attitudes influence the modern information-seeking process.
Individuals with opposing attitudes on abortion receive different search results.
Google Search engine reinforces preexisting beliefs in search results.
- Score: 0.6167267484484484
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: The evolution of information-seeking processes, driven by search engines like
Google, has transformed the access to information people have. This paper
investigates how individuals' preexisting attitudes influence the modern
information-seeking process, specifically the results presented by Google
Search. Through a comprehensive study involving surveys and information-seeking
tasks focusing on the topic of abortion, the paper provides four crucial
insights: 1) Individuals with opposing attitudes on abortion receive different
search results. 2) Individuals express their beliefs in their choice of
vocabulary used in formulating the search queries, shaping the outcome of the
search. 3) Additionally, the user's search history contributes to divergent
results among those with opposing attitudes. 4) Google Search engine reinforces
preexisting beliefs in search results. Overall, this study provides insights
into the interplay between human biases and algorithmic processes, highlighting
the potential for information polarization in modern information-seeking
processes.
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