UROP Research Mentor Project Submission Portal: Submission #1282

serial: '1282'
sid: '21006'
uuid: f892e7f3-9c3b-49f6-a673-73edd169ee8b
uri: /urop-research-mentor-project-submission-portal
created: '1755564307'
completed: '1755566609'
changed: '1756136591'
in_draft: '0'
current_page: ''
remote_addr: 179.218.246.76
uid: '0'
langcode: en
webform_id: urop_project_proposal_portal
entity_type: node
entity_id: '1116'
locked: '0'
sticky: '0'
notes: ''
metatag: meta
data:
  roundtable_info: {  }
  approximately_how_many_hours_a_week_would_the_research_assistant: '10 hours/week'
  are_you_currently_looking_for_students_: 'Yes'
  confirmation_1: '1'
  contact_email_fsu_email: ''
  contact_email_fsu_email2: ''
  contact_email_fsu_email_if_affiliated_: m.vasconcelos@fsu.edu
  faculty_advisor_confirmation: ''
  faculty_advisor_name: ''
  faculty_advisor_s_fsu_email: ''
  fsu_college: 'FAMU-FSU College of Engineering'
  fsu_department_if_applicable_: 'Electrical Engineering'
  headshot_optional_: '62756'
  if_the_project_location_is_off_campus_does_the_student_need_to_p: 'Yes'
  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.'
  mentor_handbook_and_faqs: '1'
  name_of_other_faculty_collaborator_if_applicable_: ''
  number_of_assistants_needed_faculty_postdoc_max_6_graduate_stude: '2'
  other_faculty_collaborator_s_preferred_pronouns: ''
  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).
  please_add_any_additional_information_here: ''
  please_provide_a_link_to_your_publications_a_video_clip_or_a_web: ''
  please_select_the_choice_that_most_accurately_describes_your_exp: 'Partially Remote'
  please_select_the_location_of_your_project_: 'FAMU-FSU College of Engineering'
  position_availability_for_student_research: 'Flexible schedule'
  position_title: Faculty
  primary_research_mentor_name: 'Marcos Müller Vasconcelos'
  project_keywords: 'Economics, Game Theory, Recommender Systems, Human-AI Interaction'
  relevant_student_major_s_: 'Economics, Statistics, Business, Electrical Engineering, Computer Science'
  research_mentor_preferred_pronoun2: ''
  research_mentor_pronouns: ''
  research_mentor_supervisor_if_different_from_above_: ''
  research_tasks_for_student_research_assistant_s_: |-
    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.
  roundtable_times_and_zoom_links: ''
  skills_that_research_assistants_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
  title_of_the_project: 'The Logic of the Feed: Mathematical Models of Recommender Systems in Digital Media Platforms'
  update_url: 'https://cre.fsu.edu/urop-research-mentor-project-submission-portal?element_parents=elements/research_mentor_information/headshot_optional_&ajax_form=1&_wrapper_format=drupal_ajax&token=so6g_AoUgt0PbKfOW0ylffrnT2m912sl91zwW4KY9w4'
  urop_performance_evaluation: '1'
  urop_poster_presentation: '1'
  when_potential_research_assistants_are_reaching_out_via_email_2: ''
  when_potential_research_assistants_are_reaching_out_via_email_wh: ''
  when_students_are_reaching_out_via_email_what_is_your_preferreda: Prof.
  would_you_like_to_participate_in_the_urop_research_mentor_round2: 'No'
  would_you_like_to_participate_in_the_urop_research_mentor_roundt: ''
  year: '2025'