{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-tool-for-spatio-temporal-analysis-of-social","title":"A Tool for Spatio-Temporal Analysis of Social Anxiety with Twitter Data","arxiv_id":"1901.08158","date":"2019-01-23","proceeding":null,"authors":["Joohong Lee","Dongyoung Son","Yong Suk Choi"],"abstract":"In this paper, we present a tool for analyzing spatio-temporal distribution\nof social anxiety. Twitter, one of the most popular social network services,\nhas been chosen as data source for analysis of social anxiety. Tweets (posted\non the Twitter) contain various emotions and thus these individual emotions\nreflect social atmosphere and public opinion, which are often dependent on\nspatial and temporal factors. The reason why we choose anxiety among various\nemotions is that anxiety is very important emotion that is useful for observing\nand understanding social events of communities. We develop a machine learning\nbased tool to analyze the changes of social atmosphere spatially and\ntemporally. Our tool classifies whether each Tweet contains anxious content or\nnot, and also estimates degree of Tweet anxiety. Furthermore, it also\nvisualizes spatio-temporal distribution of anxiety as a form of web\napplication, which is incorporated with physical map, word cloud, search engine\nand chart viewer. Our tool is applied to a big tweet data in South Korea to\nillustrate its usefulness for exploring social atmosphere and public opinion\nspatio-temporally.","url_abs":"http://arxiv.org/abs/1901.08158v1","url_pdf":"http://arxiv.org/pdf/1901.08158v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-tool-for-spatio-temporal-analysis-of-social","repo_url":"https://github.com/shin285/KOMORAN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}