Detecting Fraud Apps Using Sentiment Analysis

  • The proposed framework is scalable and can be extended with other domain generated evidences for ranking fraud detection.
  • Experimental results show the effectiveness of the proposed system, the scalability of the detection algorithm as well as some regularity of ranking fraud activities.
  • To the best of our knowledge, them is no existing benchmark to decide which leading sessions or Apps really contain ranking fraud. Thus, we develop four intuitive baselines and invite five human evaluators to validate.
  • Requires active internet connection.
  • System may provide inaccurate results if data entered incorrectly.

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