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Dettaglio pubblicazione

2021, Proceedings of the 2021 IEEE International Conference on Big Data (BigData 2021), Pages 1300-1307

How Inclusive Are Wikipedia’s Hyperlinks in Articles Covering Polarizing Topics? (04b Atto di convegno in volume)

Menghini Cristina, Anagnostopoulos Aris, Upfal Eli

Wikipedia relies on an extensive review process to verify that the content of each individual page is unbiased and presents a “neutral point of view.” Less attention has been paid to possible biases in the hyperlink structure of Wikipedia, which has a significant influence on the user’s exploration process when visiting more than one page. The evaluation of hyperlink bias is challenging because it depends on the global view rather than the text of individual pages. In this paper, we focus on the influence of the interconnect topology between articles describing complementary aspects of polarizing topics. We introduce a novel measure of exposure to diverse information to quantify users’ exposure to different aspects of a topic throughout an entire surfing session, rather than just one click ahead. We apply this measure to six polarizing topics (e.g., gun control and gun right), and we identify cases in which the network topology significantly limits the exposure of users to diverse information on the topic, encouraging users to remain in a knowledge bubble. Our findings demonstrate the importance of evaluating Wikipedia’s network structure in addition to the extensive review of individual articles.
ISBN: 978-1-6654-3902-2
Gruppo di ricerca: Algorithms and Data Science
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