Visual Analytics of Text Conversation Sentiment and Semantics
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2021Pay-Per-View via TIB Hannover:
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This paper describes the design and implementation of a web‐based system to visualize large collections of text conversations integrated into a hierarchical four‐level‐of‐detail design. Viewers can visualize conversations: (1) in a streamgraph topic overview for a user‐specified time period; (2) as emotion patterns for a topic chosen from the streamgraph; (3) as semantic sequences for a user‐selected emotion pattern, and (4) as an emotion‐driven conversation graph for a single conversation. We collaborated with the Live Chatcustomer service group at SAS Institute to design and evaluate our system's strengths and limitations.
BibTeX
@article {10.1111:cgf.14391,
journal = {Computer Graphics Forum},
title = {{Visual Analytics of Text Conversation Sentiment and Semantics}},
author = {Healey, Christopher G. and Dinakaran, Gowtham and Padia, Kalpesh and Nie, Shaoliang and Benson, J. Riley and Caira, Dave and Shaw, Dean and Catalfu, Gary and Devarajan, Ravi},
year = {2021},
publisher = {© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14391}
}
journal = {Computer Graphics Forum},
title = {{Visual Analytics of Text Conversation Sentiment and Semantics}},
author = {Healey, Christopher G. and Dinakaran, Gowtham and Padia, Kalpesh and Nie, Shaoliang and Benson, J. Riley and Caira, Dave and Shaw, Dean and Catalfu, Gary and Devarajan, Ravi},
year = {2021},
publisher = {© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14391}
}