SNS data Visualization for analyzing spatial-temporal distribution of social anxiety
- Title
- SNS data Visualization for analyzing spatial-temporal distribution of social anxiety
- Author
- 최용석
- Keywords
- SNS (Social Networking Service); Spatial-Temporal information; Machine Learning; Naïve Bayes Classifier; Visualization
- Issue Date
- 2016-10
- Publisher
- ACM Digital Library
- Citation
- Proceedings of the Sixth International Conference on Emerging Databases: Technologies, Applications, and Theory, v. 6, NO. 1, Page. 106-109
- Abstract
- In this paper, we describe SNS (Social Networking Service, especially Twitter) data visualization for analyzing spatial-temporal distribution of social anxiety. We prepare train data collected from Twitter by using Open API(twitter4j), which represent whether the person who post Tweet, posting message in Twitter, is anxious or not. From these data, dictionary explaining frequency of words is constructed by using KOMORAN which is Korean morphological analysis library. And we design classifier based on Naive Bayes method and estimate degree of anxiety of Tweet which include spatial-temporal information. We visualize these estimations as the form of web application, which are represented as a map and word cloud. As the spatial-temporal data are visualized in this way, we can analyze public opinion about a variety of social events.
- URI
- https://dl.acm.org/citation.cfm?doid=3007818.3007836https://repository.hanyang.ac.kr/handle/20.500.11754/81345
- ISBN
- 978-1-45-034754-9
- DOI
- 10.1145/3007818.3007836
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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