Title
Visual Analytics Of Text Conversation Sentiment And Semantics
Abstract
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.
Year
DOI
Venue
2021
10.1111/cgf.14391
COMPUTER GRAPHICS FORUM
DocType
Volume
Issue
Journal
40
6
ISSN
Citations 
PageRank 
0167-7055
0
0.34
References 
Authors
0
9