Abstract
Product and service reviews can markedly inuence consumer purchase decisions, leading to financial gains or losses for businesses. Therefore, there is a growing interest towards techniques for bringing out reviews that could negatively or positively bias new customers. To this goal, we propose a visual analysis of reviews that enables quick elicitation of interesting patterns and singularities. The proposed approach is based on a theoretically sound framework, while its effectiveness and viability is demonstrated by its application to real data extracted from Tripadvisor and Booking.com.
Original language | English (US) |
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Title of host publication | 2015 Symposium on Applied Computing, SAC 2015 |
Editors | Dongwan Shin |
Publisher | Association for Computing Machinery |
Pages | 1294-1295 |
Number of pages | 2 |
ISBN (Electronic) | 9781450331968 |
DOIs | |
State | Published - Apr 13 2015 |
Event | 30th Annual ACM Symposium on Applied Computing, SAC 2015 - Salamanca, Spain Duration: Apr 13 2015 → Apr 17 2015 |
Publication series
Name | Proceedings of the ACM Symposium on Applied Computing |
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Volume | 13-17-April-2015 |
Conference
Conference | 30th Annual ACM Symposium on Applied Computing, SAC 2015 |
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Country/Territory | Spain |
City | Salamanca |
Period | 04/13/15 → 04/17/15 |
Bibliographical note
Publisher Copyright:Copyright 2015 ACM.
Keywords
- Matrix-based visualization
- Reviews
- Singularity detection
ASJC Scopus subject areas
- Software