Social Signal Combinations in E-Commerce Reviews and Their Influence on Consumer Purchase Judgment

DOI

10.2991/978-94-6239-787-3_18How to use a DOI?

Keywords

e-commerce reviews; social signals; consumer purchase judgment; local relation patterns; online reviews; review analytics

Abstract

Online reviews influence consumer judgment in e-commerce environments, yet most existing studies focus on isolated review features such as sentiment, ratings, or helpfulness. In practice, consumers often interpret reviews through multiple social signals that appear together, including trust cues, value-related statements, risk warnings, and expressions of product fit. This paper examines how social signal combinations in e-commerce reviews are associated with consumer purchase judgment. Using the Women’s E-Commerce Clothing Reviews dataset, we identify five categories of social signals, namely bandwagon, trust, risk, value, and fit. We then construct local relation patterns based on signal co-occurrence and analyze the most frequent pairwise and triple combinations. The results show that trust- and fit-related signals dominate the review corpus, while trust-centered combinations such as Trust–Value, Trust–Fit, and especially Trust–Value–Fit exhibit the strongest positive associations with recommendation tendency and positive rating outcomes. In contrast, patterns involving risk signals are less frequent and show weaker or negative associations. These findings suggest that consumer judgment is better explained by structured multi-signal patterns than by single review cues alone. The study provides an interpretable framework for understanding review-based decision processes and offers implications for review presentation and e-commerce platform design.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zijia Liu
AU  - Yan Zhang
PY  - 2026
DA  - 2026/09/29
TI  - Social Signal Combinations in E-Commerce Reviews and Their Influence on Consumer Purchase Judgment
BT  - Proceedings of the 2026 4th International Conference on Management Innovation and Economy Development (MIED 2026)
PB  - Atlantis Press
SP  - 159
EP  - 167
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-787-3_18
DO  - 10.2991/978-94-6239-787-3_18
ID  - Liu2026
ER  -