Cognitive Assistant Protocol Selection For Emergency Response Situations; Comparison of The Motivations Behind Facebook Users And TikTok Users

Guevarra, Renzo, School of Engineering and Applied Science, University of Virginia
Ku, Tsai-Hsuan, EN-Engineering and Society, University of Virginia
Alemzadeh, Homa, Electrical & Computer Engineering, University of Virginia

Emergency response situations require quick thinking and critical decision making. One
wrong decision or a second of hesitation from an emergency responder can result in major
consequences. My technical research dives deep into a modular component of a cognitive
assistant for emergency response which intends to improve situational awareness and safety of
first responders by real-time collection and analysis of data from the incident scene and provide
dynamic-driven feedback to them. My research specifically focuses on how to improve
the performance of the protocol selection modular component.

Knowing the user motivation and psychology behind different social media platforms can
play a huge role on how future social media algorithms will develop in the future. My STS
research focuses specifically on comparing Facebook and TikTok in terms of each respective
platform’s users, purposes of spending on time, the friendships defined, the algorithm and user
interfaces, and how the respective algorithm designs attract different users.

The technical subject of the STS prospectus and the technical topic for the Dept. of
Computer Science is not related.

BS (Bachelor of Science)
TikTok, Facebook, SCOT, Mediation Theory, Protocol Selection, Emergency Response Situations, User Motivation

School of Engineering and Applied Science

Bachelor of Science in Computer Science

Technical Advisor: Homa Alemzadeh

STS Advisor: Tsai-Hsuan Ku

Technical Team Members:

Issued Date: