UROP Research Mentor Project Submission Portal: Submission #930
Submission information
Submission Number: 930
Submission ID: 15276
Submission UUID: 31e4328d-c8b1-4fc1-a221-037e63382374
Submission URI: /urop-research-mentor-project-submission-portal
Submission Update: /urop-research-mentor-project-submission-portal?token=BiFgmA-Vx7z1zE01ftJ50obomzgIPazVsspCEvh9JzE
Created: Mon, 08/19/2024 - 11:12 PM
Completed: Mon, 08/19/2024 - 11:14 PM
Changed: Mon, 08/26/2024 - 02:17 PM
Remote IP address: 217.180.192.191
Submitted by: Anonymous
Language: English
Is draft: No
Webform: UROP Project Proposal Portal
Submitted to: UROP Research Mentor Project Submission Portal
Research Mentor Information
Yimeng Li
he/him
Dr.
Post Doc
Social Sciences and Public Policy
Political Science
{Empty}
Additional Research Mentor(s)
Overall Project Details
Analyzing Candidate Characteristics and Electoral Performance
Candidate Characteristics; Electoral Performance; Voting Behavior; Information Cues
Yes
2
Open to all majors, but prefer Political Science majors
On FSU Main Campus
{Empty}
Partially Remote
5-10
Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
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.
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.
(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.
(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.
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.
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.
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.
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.
https://yimeng-li.com/all_research/
{Empty}
No
{Empty}
UROP Program Elements
Yes
Yes
Yes
Yes
{Empty}
2024
https://cre.fsu.edu/urop-research-mentor-project-submission-portal?token=BiFgmA-Vx7z1zE01ftJ50obomzgIPazVsspCEvh9JzE