“Do not deceive me anymore!” interpretation through model design and visualization for instagram counterfeit seller account detection
- Title
- “Do not deceive me anymore!” interpretation through model design and visualization for instagram counterfeit seller account detection
- Author
- 박정은
- Keywords
- Deep learning; User experience; Instagram; Social problem; Multimodal ensemble model; Explainable artificial intelligence
- Issue Date
- 2022-08-06
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Citation
- COMPUTERS IN HUMAN BEHAVIOR, v. 137, article no. 107418, page. 1-26
- Abstract
- Counterfeit goods sold online have amounted to $330 billion in losses worldwide. Of these, luxury brand losses account for $30.3 billion. The social and economic effects of counterfeit goods have become more severe with the shift of counterfeit sales channels to social networking services (SNSs) since the first decade of the 2000s when these networks became active. In particular, the number of counterfeit sellers on Instagram increased by more than 171% in 2019. This study endeavors to detect counterfeit seller accounts in the SNS environment through a deep learning method that implements an algorithm to differentiate legitimate and counterfeit seller accounts. We designed a model to classify counterfeit seller accounts and general accounts using image and textual data collected from Instagram. As a result, the proposed model obtained a final account detection accuracy of 100% and demonstrated the possibility of use as a counterfeit seller account detector. Moreover, the elements that influenced the results and the parts that the model focused on were identified using a visual analysis method to improve the interpretation capability of the algorithm and explain the results. The difference between human and machine judgments was analyzed based on the visualization.
- URI
- https://www.sciencedirect.com/science/article/pii/S0747563222002400https://repository.hanyang.ac.kr/handle/20.500.11754/191074
- ISSN
- 0747-5632
- DOI
- https://doi.org/10.1016/j.chb.2022.107418
- Appears in Collections:
- COLLEGE OF COMPUTING[E](소프트웨어융합대학) > MEDIA, CULTURE, AND DESIGN TECHNOLOGY(ICT융합학부) > Articles
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML