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Register a new userAuditing Wikipedias Hyperlinks Network on Polarizing Topics
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Added by
Cristina Menghini
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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People eager to learn about a topic can access Wikipedia to form a preliminary opinion. Despite the solid revision process behind the encyclopedias articles, the users exploration process is still influenced by the hyperlinks network. In this paper, we shed light on this overlooked phenomenon by investigating how articles describing complementary subjects of a topic interconnect, and thus may shape readers exposure to diverging content. To quantify this, we introduce the exposure to diverse information, a metric that captures how users exposure to multiple subjects of a topic varies click-after-click by leveraging navigation models. For the experiments, we collected six topic-induced networks about polarizing topics and analyzed the extent to which their topologies induce readers to examine diverse content. More specifically, we take two sets of articles about opposing stances (e.g., guns control and guns right) and measure the probability that users move within or across the sets, by simulating their behavior via a Wikipedia-tailored model. Our findings show that the networks hinder users to symmetrically explore diverse content. Moreover, on average, the probability that the networks nudge users to remain in a knowledge bubble is up to an order of magnitude higher than that of exploring pages of contrasting subjects. Taken together, those findings return a new and intriguing picture of Wikipedias network structural influence on polarizing issues exploration.
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