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First I "like" it, then I hide it: Folk Theories of Social Feeds

Published: 07 May 2016 Publication History

Abstract

Many online platforms use curation algorithms that are opaque to the user. Recent work suggests that discovering a filtering algorithm's existence in a curated feed influences user experience, but it remains unclear how users reason about the operation of these algorithms. In this qualitative laboratory study, researchers interviewed a diverse, non-probability sample of 40 Facebook users before, during, and after being presented alternative displays of Facebook's News Feed curation algorithm's output. Interviews revealed 10 "folk theories' of automated curation, some quite unexpected. Users who were given a probe into the algorithm's operation via an interface that incorporated "seams,' visible hints disclosing aspects of automation operations, could quickly develop theories. Users made plans that depended on their theories. We conclude that foregrounding these automated processes may increase interface design complexity, but it may also add usability benefits.

Supplementary Material

ZIP File (pn2272-file4.zip)
The auxiliary material consist of the interview protocol (four pdf files): the initial survey protocol, the pre-probe interview protocol, the probe interview protocol, and the post-probe interview protocol.
suppl.mov (pn2272.mp4)
Supplemental video

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  1. First I "like" it, then I hide it: Folk Theories of Social Feeds

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    cover image ACM Conferences
    CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
    May 2016
    6108 pages
    ISBN:9781450333627
    DOI:10.1145/2858036
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 07 May 2016

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    Author Tags

    1. algorithms
    2. folk theories
    3. seamful design
    4. social media feeds

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    • the University of Illinois Office of Vice Chancellor for Research.

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    May 7 - 12, 2016
    California, San Jose, USA

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    Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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    • (2024)Cross-platform sensitivity and algorithmic adaptability: How transnational creators navigate algorithms across Chinese and US-based platformsNew Media & Society10.1177/14614448241307578Online publication date: 22-Dec-2024
    • (2024)ChatGPT in the public eye: Ethical principles and generative concerns in social media discussionsNew Media & Society10.1177/14614448241279034Online publication date: 21-Sep-2024
    • (2024)Moral orders of pleasing the algorithmNew Media & Society10.1177/14614448241278674Online publication date: 11-Sep-2024
    • (2024)The artificial intelligence divide: Who is the most vulnerable?New Media & Society10.1177/14614448241232345Online publication date: 26-Feb-2024
    • (2024)De- and recoding algorithmic systems: The case of fact checkers and fact checked usersConvergence: The International Journal of Research into New Media Technologies10.1177/13548565241289233Online publication date: 23-Oct-2024
    • (2024)If you’re reading this, it’s meant for you: The reflexive ambivalence of algorithmic conspiritualityConvergence: The International Journal of Research into New Media Technologies10.1177/13548565241258949Online publication date: 3-Jun-2024
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    • (2024)When the "Matchmaker" Does Not Have Your Interest at Heart: Perceived Algorithmic Harms, Folk Theories, and Users' Counter-Strategies on TinderProceedings of the ACM on Human-Computer Interaction10.1145/36897108:CSCW2(1-29)Online publication date: 8-Nov-2024
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