Date of Graduation

5-2022

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Psychology (PhD)

Degree Level

Graduate

Department

Psychological Science

Advisor/Mentor

Beike, Denise R.

Committee Member

Makhanova, Anastasia

Second Committee Member

Eidelman, Scott H.

Keywords

Algorithms; Experimental psychology; Online communication; Social media; Social psychology

Abstract

The public’s turn towards news websites and social media for news consumption has sparked anxiety over echo chambers, avoidance of opinion-challenging content, and potentially fragmentation and polarization among sociopolitical groups. Algorithms have specifically been blamed for increasing the ease of filtering out counter-attitudinal online content and potentially exacerbating selective exposure tendencies. However, longstanding classic psychological research has demonstrated the ubiquitous phenomenon of cognitive dissonance and selective exposure far before the internet became the primary tool for news consumption. Research investigating how algorithms directly influence online approach and avoidance behavior is unfortunately scarce. This dissertation work aimed to analyze the impact of an algorithm system during online information consumption on selective exposure behavior. Participants were randomly assigned to one of three conditions: a neutral condition where presented articles are balanced in attitudinal valence; an algorithm condition where presented articles update to match previous selection behavior; and a motivated condition where participants are encouraged to explore dissimilar viewpoints. Overall, a-priori hypotheses were not supported, and condition had virtually no effect on dependent variables, including selective exposure tendency. However, results provide an in-depth look into perceptual and behavioral processes of highly polarized individuals during the information-seeking process.

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