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Co-Bridges: Pair-wise Visual Connection and Comparison for Multi-item Data Streams

Chen, S., Andrienko, N. ORCID: 0000-0003-3313-1560, Andrienko, G. ORCID: 0000-0002-8574-6295, Li, J. and Yuan, X. (2020). Co-Bridges: Pair-wise Visual Connection and Comparison for Multi-item Data Streams. IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/TVCG.2020.3030411

Abstract

In various domains, there are abundant streams or sequences of multi-item data of various kinds, e.g. streams of news and social media texts, sequences of genes and sports events, etc. Comparison is an important and general task in data analysis. For comparing data streams involving multiple items (e.g., words in texts, actors or action types in action sequences, visited places in itineraries, etc.), we propose Co-Bridges, a visual design involving connection and comparison techniques that reveal similarities and differences between two streams. Co-Bridges use river and bridge metaphors, where two sides of a river represent data streams, and bridges connect temporally or sequentially aligned segments of streams. Commonalities and differences between these segments in terms of involvement of various items are shown on the bridges. Interactive query tools support the selection of particular stream subsets for focused exploration. The visualization supports both qualitative (common and distinct items) and quantitative (stream volume, amount of item involvement) comparisons. We further propose Comparison-of-Comparisons, in which two or more Co-Bridges corresponding to different selections are juxtaposed. We test the applicability of the Co-Bridges in different domains, including social media text streams and sports event sequences. We perform an evaluation of the users' capability to understand and use Co-Bridges. The results confirm that Co-Bridges is effective for supporting pair-wise visual comparisons in a wide range of applications.

Publication Type: Article
Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Visual Comparison, Pair-wise Analysis, Multi-item Data Stream, Social Media
Subjects: H Social Sciences > HM Sociology
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science > giCentre
Date Deposited: 09 Nov 2020 15:06
URI: https://openaccess.city.ac.uk/id/eprint/25207
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