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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Measuring Crowd Mood in City Space Through Twitter
verfasst von : Shoko Wakamiya, Lamia Belouaer, David Brosset, Ryong Lee, Yukiko Kawai, Kazutoshi Sumiya, Christophe Claramunt
Erschienen in: Web and Wireless Geographical Information Systems
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In this paper, we measure crowd mood and investigate its spatio-temporal distributions in a large-scale urban area through Twitter. In order to exploit tweets as a source to survey crowd mind, we propose two measurements which extract and categorize semantic terms from texts of tweets based on a dictionary of emotional terms. In particular, we focus on how to aggregate crowd mood quantitatively and qualitatively. n the experiment, the proposed methods are applied to a large tweets dataset collected for an urban area in Japan. From the daily tweets, we were able to observe interesting temporal changes in crowd’s positive and negative moods and also identified major downtown areas where crowd’s emotional tweets are intensively found. In this preliminary work, we confirme the diversity of urban areas in terms of crowd moods which are observed from the crowd-sourced lifelogs on Twitter.