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Editor’s Introduction

Vladimir Zwass

International Journal of Electronic Commerce2025https://doi.org/10.1080/10864415.2025.2471670article
AJG 3ABDC A
Weight
0.50

Abstract

professionals, doctors among them.Here, Wenchao Du, Yabin Yang.Xitong Guo, and Doug Vogel present their investigation of the impact of the engagement of these professionals in social media on the returns from their practice.The results are highly encouraging to those who would skillfully employ these media for personal branding-across the professions and trades.Fake reviews are the bane of e-commerce.In spite of the elaborate measures taken against them, they do proliferate.In the concluding paper of the issue, Wei Du, Jianlan Li, Jilei Zhou, Qi Lu, and Yue San deploy deep learning to combat multimodal fakes, those that combine text and images.It should be noted that the inclusion of images may increase the believability of such reviews, and thus this work is an important contribution to the extensive research regarding online reviews in our field.The authors combine the intramodal detection techniques (text and images separately) with the multimodal ones.With a real-world dataset, the researchers demonstrate the effectiveness of their method in the detection of fake reviews.

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https://doi.org/https://doi.org/10.1080/10864415.2025.2471670

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@article{vladimir2025,
  title        = {{Editor’s Introduction}},
  author       = {Vladimir Zwass},
  journal      = {International Journal of Electronic Commerce},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/10864415.2025.2471670},
}

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Editor’s Introduction

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.