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Examination of Social Media Algorithms’ Ability to Know User Preferences

Barrera Corrales, Daniel
http://rave.ohiolink.edu/etdc/view?acc_num=oduhonors1682966000440837

Abstract Details

2023, Honors Theses, Ohio Dominican University, Honors Theses.
Algorithms are used by social media platforms to gather information on users to better suggest updated content to maximize the time spent on their online platforms. The information gathered from the users (browsing history, search history, engaged posts, engaged channels, etc.) is analyzed by these algorithms and used to predict what content and channels to best offer the users for further engagement. Information such as liking patterns, following tendencies, content engagement behavior and more are fed to these algorithms to personalize the user’s experience. The goal of this paper is to compare the effectiveness of the algorithms’ ability to profile and induce users, in this case employed by Instagram, Twitter, and YouTube by tracking several variables, including interaction time and interaction rates with posts, channels, likes, and follows. The results of this study show the performance of each platform algorithm over weeks of observation and how they stack in terms of engagement effectiveness.
Alae Loukili (Advisor)
Kristall Day (Other)
Kenneth Fah (Other)
22 p.
Computer Engineering; Computer Science
Algorithms; Personalization; Social Media; Marketing; Media Personalization; Online Privacy; Recommender Systems; Automated Decision Making; Artificial Intelligence; Service Marketing; Content Moderation

Recommended Citations

Citations

  • Barrera Corrales, D. (2023). Examination of Social Media Algorithms’ Ability to Know User Preferences [Electronic thesis or dissertation, Ohio Dominican University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=oduhonors1682966000440837

    APA Style (7th edition)

  • Barrera Corrales, Daniel. Examination of Social Media Algorithms’ Ability to Know User Preferences. 2023. Ohio Dominican University, Electronic thesis or dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=oduhonors1682966000440837.

    MLA Style (8th edition)

  • Barrera Corrales, Daniel. "Examination of Social Media Algorithms’ Ability to Know User Preferences." Electronic thesis or dissertation, Ohio Dominican University, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=oduhonors1682966000440837

    Chicago Manual of Style (17th edition)

oduhonors1682966000440837
274
© 2023, all rights reserved.
This open access ETD is published by Ohio Dominican University Honors Theses and OhioLINK.