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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.
With YouTubes growing importance as a news platform, its recommendation system came under increased scrutiny. Recognizing YouTubes recommendation system as a broadcaster of media, we explore the applicability of laws that require broadcasters to give
The 2020 coronavirus pandemic was a historic social disruption with significant consequences felt around the globe. Wikipedia is a freely-available, peer-produced encyclopedia with a remarkable ability to create and revise content following current e
The large-scale online management systems (e.g. Moodle), online web forums (e.g. Piazza), and online homework systems (e.g. WebAssign) have been widely used in the blended courses recently. Instructors can use these systems to deliver class content a
While links in simple networks describe pairwise interactions between nodes, it is necessary to incorporate hypernetworks for modeling complex systems with arbitrary-sized interactions. In this study, we focus on the hyperlink prediction problem in h
A patient-centric approach to healthcare leads to an informal social network among medical professionals. This chapter presents a research framework to: identify the collaboration structure among physicians that is effective and efficient for patient