UROP Research Mentor Project Submission Portal: Submission #1282 | Center for Undergraduate Research and Academic Engagement

Submission information

Submission Number: 1282

Submission ID: 21006

Submission UUID: f892e7f3-9c3b-49f6-a673-73edd169ee8b

Submission URI: /urop-research-mentor-project-submission-portal

Submission Update: /urop-research-mentor-project-submission-portal?token=so6g_AoUgt0PbKfOW0ylffrnT2m912sl91zwW4KY9w4

Created: Mon, 08/18/2025 - 08:45 PM

Completed: Mon, 08/18/2025 - 09:23 PM

Changed: Mon, 08/25/2025 - 11:43 AM

Remote IP address: 179.218.246.76

Submitted by: Anonymous

Language: English

Is draft: No

Webform: UROP Project Proposal Portal

Submitted to: UROP Research Mentor Project Submission Portal

Research Mentor Information

Primary Research Mentor Name Marcos Müller Vasconcelos

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When potential research assistants are reaching out via email, what is your preferred honorific? Prof.

Contact Email (FSU Email if affiliated) m.vasconcelos@fsu.edu

Position Title Faculty

FSU College (if applicable) FAMU-FSU College of Engineering

FSU Department or Non-FSU Organization Affiliation Electrical Engineering

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Additional Research Mentor(s)

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Overall Project Details

Title of the Project The Logic of the Feed: Mathematical Models of Recommender Systems in Digital Media Platforms

Project Keywords Economics, Game Theory, Recommender Systems, Human-AI Interaction

Are you currently looking for research assistants? Yes

Number of Research Assistants Needed 2

Relevant Research Assistant Major(s) Economics, Statistics, Business, Electrical Engineering, Computer Science

Project Location: FAMU-FSU College of Engineering

If the project location is off campus, does the research assistant(s) need to provide their own transportation? Yes

Please select the choice that most accurately describes your expectations for the research assistant(s): Partially Remote

Approximately how many hours a week would the research assistant(s) need to work? 10 hours/week

Roughly what time frame do you expect research assistant(s) to work? Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)

Overall Research Project Description Most information consumed online today flows through digital media platforms such as YouTube, TikTok, and Instagram. Because the volume of available content is overwhelming, these platforms rely on recommendation systems to filter and promote material. However, recommendations are made under uncertainty: platforms cannot directly observe a user’s private preferences. Instead, they adapt their strategies to maximize engagement, even if it means amplifying extreme or polarized content. Our recent research has modeled this interaction as a signaling game between a platform and a user: the user seeks content aligned with their preferences, while the platform seeks to maximize engagement regardless of alignment. Theoretical results show that equilibrium strategies in such games can naturally lead to the escalation of extreme content availability. This raises important questions about how algorithms, user behavior, and economic incentives jointly shape the online information ecosystem.

Objectives:

This UROP project aims to explore recommender systems by focusing on three interconnected areas:

1. Algorithmic Foundations – how recommendation strategies influence exposure to extreme versus moderate content.

2. User Behavior & Engagement – how individuals respond to content depending on alignment and private preferences.

3. Economic & Game-Theoretic Aspects – how engagement-driven incentives can lead to unintended outcomes, such as polarization and escalation of content intensity.

This is a joint project with professors from the University of Southern California (USC).

Research Tasks 1. Simulation & Modeling: Build simplified game-theoretic or agent-based models of user–platform interactions, exploring equilibrium dynamics.

2. Data Analysis: Use small-scale datasets (e.g., Reddit, Twitter/X, or simulated feeds) to study recommendation patterns and engagement responses.

3. Theoretical Exploration: Extend the signaling game framework to test how assumptions (e.g., user heterogeneity, platform objectives) affect equilibrium outcomes.

Skills that research assistant(s) may need: Students should have:

1. Basic programming (Python, MATLAB, or R) - recommended

2. Probability/statistics background - recommended

3. Interest in digital media, algorithms, and game theory - required

Mentoring Philosophy Our mentoring philosophy centers on empowering students to gain confidence in their ideas and nurturing their creativity. At the MINDS lab, we embrace the motto that there is no limit to what the human mind can accomplish and that the world of ideas offers an infinite number of low-hanging fruits. Currently, our lab has supported a diverse group of researchers, including many undergraduates, two PhD students, and one postdoc. We believe that a diverse team, representing a wide spectrum of backgrounds and perspectives, leads to more innovative work, thereby contributing to the broadening of participation of underrepresented groups in the scientific community and society as a whole.

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Are you interested in participating in the UROP Research Mentor Roundtable? No

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UROP Program Elements

Mentor Handbook, FAQs, and Communication Yes

UROP Performance Evaluation Yes

Materials Grant Yes

UROP Poster Presentation Yes

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Year 2025

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