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Title:Designing technologies for exposure to diverse opinions
Author(s):Liao, Qingzi
Director of Research:Fu, Wai-Tat
Doctoral Committee Chair(s):Fu, Wai-Tat
Doctoral Committee Member(s):Kirlik, Alex; Schatz, Bruce; Pirolli, Peter
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):selective exposure
online deliberation
diversity-enhancing technology
confirmation bias
Abstract:Exposure to diverse opinions can help individuals develop accurate beliefs, make better decisions, and become more understanding and tolerant persons. It is also necessary for the governance of a stable and democratic society. However, the exposure is often limited by people's natural tendency towards selective exposure—preferential seeking of confirmatory over challenging information. This has prompted many scholars to warn about the rise of "echo chambers" and "filter bubbles" online, with individuals' easy control over information exposure enabled by digital technologies. Such concern has motivated HCI researchers to study a class of diversity-enhancing technologies—information and social technologies that host diverse viewpoints and take increasing users' exposure to information that challenges their existing beliefs as a design goal. In this dissertation, I seek to answer the following question: What kind of design features can nudge users to be exposed to more attitude-challenging information? To complement the current technical-HCI approaches, I focus on bridging social science theories on selective exposure and design guidelines for diversity-enhancing technologies. Specifically, the central objective of this dissertation is to understand the key factors that moderate individuals' propensity to engage in selective exposure in interacting with information and social technologies and apply the knowledge in four aspects of diversity-enhancing technology design: 1) design by enabling the moderators that reduce, and eliminating ones that increase, selective exposure; 2) design for personalization by identifying user groups and use contexts that have varied selective exposure tendencies; 3) design for personalization by tailoring diversity-enhancing designs based on the underlying individual differences; and 4) design beyond individuals by considering the opinion group differences in selective exposure tendencies and the implication for user behaviors and social network structure. This dissertation provides empirical evidence that user behaviors in seeking attitude-relevant information are subject to the influence of various individual and contextual factors and recommends a more personalized approach that carefully controls and leverages these factors to nudge users into more desirable information consumption. It contributes several new lessons for designing technologies that present diverse viewpoints, including a theory-driven guideline for personalizing diversity-enhancing designs, insights on the selective exposure bias in consumer health information seeking, and an exploration of group selective exposure and its implication for social technology design. Perhaps most importantly, the dissertation pinpoints several directions in which selective exposure theories can be applied to the design of diversity-enhancing technologies, which opens up opportunities for developing a unified knowledge framework to push this research field forward.
Issue Date:2016-12-01
Rights Information:Copyright 2016 Qingzi Liao
Date Available in IDEALS:2017-03-01
Date Deposited:2016-12

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