{"id":{"repo_id":"cuny-grad","oai_identifier":"oai:academicworks.cuny.edu:gc_etds-5933"},"canonical_url":"https://search.dev.ndltd.org/etd/cuny-grad/oai:academicworks.cuny.edu:gc_etds-5933","repository":{"repo_id":"cuny-grad","name":"City University of New York - Graduate Center","base_url":"https://academicworks.cuny.edu/do/oai/"},"display":{"title":"Why, New York City? Gauging the Quality of Life Through the Thoughts of Tweeters","abstract":"<p>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.</p> <p>GitHub Repository for all the files: <a href=\"https://github.com/shewilliams/whynyc\">https://github.com/shewilliams/whynyc</a>.<br />Website: <a href=\"https://shewilliams.github.io/whynyc/\">https://shewilliams.github.io/whynyc/</a>.</p>","abstract_html":"&lt;p&gt;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.&lt;/p&gt; &lt;p&gt;GitHub Repository for all the files: &lt;a href=&quot;https://github.com/shewilliams/whynyc&quot;&gt;https://github.com/shewilliams/whynyc&lt;/a&gt;.&lt;br /&gt;Website: &lt;a href=&quot;https://shewilliams.github.io/whynyc/&quot;&gt;https://shewilliams.github.io/whynyc/&lt;/a&gt;.&lt;/p&gt;","abstract_has_math":false,"creators":["Williams, Sheryl"],"institution":"The Graduate School and University Center of The City University of New York","degree_name":"Master of Science","degree_level":"Master","degree_discipline":"Data Analysis & Visualization","degree_department":null,"school":null,"contributors":[],"advisors":["Timothy Shortell"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-06-01T07:00:00Z","date_published":"2022-06-01T07:00:00Z","updated_at":"2026-07-24T01:58:22Z","subjects":["Categorical Data Analysis","Data Science","Geographic Information Sciences","Graphic Communications","Social and Cultural Anthropology","Social Influence and Political Communication","Social Media","topic modeling","sentiment analysis","geographic analysis","data visualization","twitter","new york city","los angeles"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://academicworks.cuny.edu/gc_etds/4898","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Timothy Shortell"]},{"key":"dc:creator","label":"Author","values":["Williams, Sheryl"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2022-04-27T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Data Analysis & Visualization"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Master"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The Graduate School and University Center of The City University of New York"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Categorical Data Analysis","Data Science","Geographic Information Sciences","Graphic Communications","Social and Cultural Anthropology","Social Influence and Political Communication","Social Media","topic modeling","sentiment analysis","geographic analysis","data visualization","twitter","new york city","los angeles"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://academicworks.cuny.edu/gc_etds/4898"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>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.</p> <p>GitHub Repository for all the files: <a href=\"https://github.com/shewilliams/whynyc\">https://github.com/shewilliams/whynyc</a>.<br />Website: <a href=\"https://shewilliams.github.io/whynyc/\">https://shewilliams.github.io/whynyc/</a>.</p>"]},{"key":"dc:title","label":"Title","values":["Why, New York City? Gauging the Quality of Life Through the Thoughts of Tweeters"]}]}],"canonical_facts":{"dc:contributor.advisor":["Timothy Shortell"],"dc:creator":["Williams, Sheryl"],"dc:date.available":["2022-04-27T07:00:00Z"],"dc:description.abstract":["<p>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.</p> <p>GitHub Repository for all the files: <a href=\"https://github.com/shewilliams/whynyc\">https://github.com/shewilliams/whynyc</a>.<br />Website: <a href=\"https://shewilliams.github.io/whynyc/\">https://shewilliams.github.io/whynyc/</a>.</p>"],"dc:identifier":["https://academicworks.cuny.edu/gc_etds/4898"],"dc:subject":["Categorical Data Analysis","Data Science","Geographic Information Sciences","Graphic Communications","Social and Cultural Anthropology","Social Influence and Political Communication","Social Media","topic modeling","sentiment analysis","geographic analysis","data visualization","twitter","new york city","los angeles"],"dc:title":["Why, New York City? 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