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About Detection of Fraud Apps Using Sentiment Analysis: Abstract
This document discusses detection of fraud apps using sentiment analysis. It proposes a framework to identify ranking fraud in the mobile app market, which refers to fraudulent practices used by some app developers to increase their app's ranking. The framework examines ranking-based, rating-based, and review-based metrics to detect inconsistencies that may indicate fraud. It aims to implement this framework using Android Studio with a minimum hardware specification of 3GB RAM and 1280x800 screen resolution. A literature review discusses previous work on detecting fake reviews and hybrid shilling attacks used to influence ratings. The proposed technique is intended to help customers make informed choices and prevent spamming practices from impacting app rankings.
Detailed Information
| Author: | ['chinmai'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 4 |
| Language: | English |
| Format: | |
| Price: | FREE |
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