UROP Project
Candidate Characteristics; Electoral Performance; Voting Behavior; Information Cues
Research Mentor: Dr. Yimeng Li, he/him
Department, College, Affiliation: Political Science, Social Sciences and Public Policy
Contact Email: yimeng.li@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators: Mr. Austin Cutler
Faculty Collaborators Email: acutler@fsu.edu
Department, College, Affiliation: Political Science, Social Sciences and Public Policy
Contact Email: yimeng.li@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators: Mr. Austin Cutler
Faculty Collaborators Email: acutler@fsu.edu
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Open to all majors, but prefer Political Science majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10,
Roundtable Times and Zoom Link: Not participating in the Roundtable
Number of Research Assistants: 2
Relevant Majors: Open to all majors, but prefer Political Science majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10,
Roundtable Times and Zoom Link: Not participating in the Roundtable
Project Description
In this project, we seek to analyze the association between candidate characteristics and electoral performance in primary and general elections. Candidate characteristics such as age, gender, and race provide important information cues in addition to their party affiliation and policy positions in voter’s choice, especially in low information contests.In this project, we first expand national and state databases on candidate information and election results at low aggregation. This step involves scraping data from state and county websites and searching newspaper databases. We then use computer programs to clean the data and build databases for subsequent analyses.
In the second part of the project, we conduct statistical analyses to determine the association between candidate characteristics and electoral performance in low and high-information environments. This step involves both simple regression analysis and advanced ecological inferences. We finally compare the results with experimental evidence in the literature.
Research Tasks: (Data Collection) Research assistants will expand national and state databases on candidate information and election results at low aggregation. This step involves scraping data from state and county websites to obtain electoral performance data. It also requires extracting from candidate bios and searching newspaper databases to obtain information on candidate characteristics.
(Data Analysis) Research assistants will conduct statistical analyses to determine the association between candidate characteristics and electoral performance. Research assistants will learn to use R to generate simple summary statistics, conduct data visualization, and run regression analyses.
Skills that research assistant(s) may need: Proficiency with Microsoft Excel. Attention to detail is critical to this project.
Preferences will be given to political science sophomores who have completed or are taking POS 1041 American National Government. Preferences will be given to students with strong academic records, evidenced in their CVs and transcripts.
Mentoring Philosophy
Every mentee is different. I will identify each mentee’s goals, aspirations, and existing knowledge. I will try to help mentees achieve their goals and aspirations through the mentoring process. I will accommodate the assigned work schedule that fits the mentee’s other classes and activities.Communication is key. I will establish clear expectations with the mentee at the beginning of the mentorship and maintain weekly meetings to discuss progress and challenges encountered.