Date of Degree

6-2022

Document Type

Capstone Project

Degree Name

M.S.

Program

Data Analysis & Visualization

Advisor

Timothy Shortell

Subject Categories

Categorical Data Analysis | Data Science | Geographic Information Sciences | Graphic Communications | Social and Cultural Anthropology | Social Influence and Political Communication | Social Media

Keywords

topic modeling, sentiment analysis, geographic analysis, data visualization, twitter, new york city, los angeles

Abstract

As a resource for social data, Twitter’s platform has been used to measure the quality of life through sentiment analysis. This capstone project explores another methodological technique—querying Twitter data around specific keyword terms to determine dominant topics, word patterns, and sentiment leanings in a geographical area. Focusing on New York City and Los Angeles for comparative analysis, the keyword term “why” will be used to build a Python analysis around topic modeling and sentiment analysis. Using this approach, the analysis reveals social and cultural differences, the overall sentiment of tweets, and subjects of interest to tweeters.

GitHub Repository for all the files: https://github.com/shewilliams/whynyc.
Website: https://shewilliams.github.io/whynyc/.

Comments

Online component: https://shewilliams.github.io/whynyc/

whynyc.zip (209024 kB)
File contains Python and website files

sheryl-williams-2022-capstone-project-20220531185505.warc (7824 kB)
Archived version of project website

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