Abstract
Researchers across many fields are increasingly using data from social media sites to address questions about individual and group social behaviors. However, the size and complexity of these data sets challenge traditional research methods; many new tools and techniques have been developed to support research in this area. In this paper, we present our experience designing and evaluating Agave, a collaborative visual analysis system for exploring events and sentiment over time in large tweet data sets. We offer findings from evaluating Agave with researchers experienced with social media data, focusing on how users interpreted sentiment labels shown in the interface and on the value of collaboration for stimulating exploratory analysis.
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© 2014 Springer International Publishing Switzerland
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Brooks, M., Robinson, J.J., Torkildson, M.K., Hong, S.(., Aragon, C.R. (2014). Collaborative Visual Analysis of Sentiment in Twitter Events. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2014. Lecture Notes in Computer Science, vol 8683. Springer, Cham. https://doi.org/10.1007/978-3-319-10831-5_1
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DOI: https://doi.org/10.1007/978-3-319-10831-5_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10830-8
Online ISBN: 978-3-319-10831-5
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