Abstract: In this paper, we present a tool for analyzing spatio-temporal distributionof social anxiety. Twitter, one of the most popular social network services,has been chosen as data source for analysis of social anxiety. Tweets (postedon the Twitter) contain various emotions and thus these individual emotionsreflect social atmosphere and public opinion, which are often dependent onspatial and temporal factors. The reason why we choose anxiety among variousemotions is that anxiety is very important emotion that is useful for observingand understanding social events of communities. We develop a machine learningbased tool to analyze the changes of social atmosphere spatially andtemporally. Our tool classifies whether each Tweet contains anxious content ornot, and also estimates degree of Tweet anxiety. Furthermore, it alsovisualizes spatio-temporal distribution of anxiety as a form of webapplication, which is incorporated with physical map, word cloud, search engineand chart viewer. Our tool is applied to a big tweet data in South Korea toillustrate its usefulness for exploring social atmosphere and public opinionspatio-temporally.
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From: Joohong Lee [view email]1,834 Followers, 356 Following, 368 Posts - See Instagram photos and videos from Joohong (@joohong). Free Download JOOX app on iOS, Android and Desktop (Windows/Mac), enjoy high quality music experience anytime, anywhere.
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