Summary of Scamspot: Fighting Financial Fraud in Instagram Comments, by Stefan Erben and Andreas Waldis
ScamSpot: Fighting Financial Fraud in Instagram Comments
by Stefan Erben, Andreas Waldis
First submitted to arxiv on: 14 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed ScamSpot system aims to combat spam and fraudulent messages in Instagram comment sections, a persistent problem plaguing the financial sector. The current spam filter is ineffective, and existing research lacks practical implementations with evaluated results. ScamSpot consists of a browser extension, fine-tuned BERT model, and REST API, making it publicly accessible for Chrome users. A data annotation study is conducted to understand the causes of the issue, and the system is evaluated through user feedback and comparison with existing models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Instagram’s comment sections are plagued by spam and fraudulent messages, causing financial losses and credibility issues. To combat this problem, researchers propose ScamSpot, a comprehensive system combining a browser extension, BERT model, and REST API. This open-source project makes it easy for users to access the results. The paper also includes a study on why this problem exists and how well ScamSpot works. |
Keywords
* Artificial intelligence * Bert
