Google has rolled out enhancements to Google Play by introducing improved detection and filtering mechanisms in a bid to combat fraud and spam installations. According to sources, the main aim of the update is to prevent app developers from deliberately boosting the popularity of apps.
The end result of the new detection and filtering technology is to enable users to discover deserving apps. Moreover, the update will showcase the creations and offerings of developers in a better way.
New filtering mechanism will reduce manipulation
In a statement via a blog post on the Android Developers Blog, the search-engine giant revealed that the company is hopeful that the new mechanism will reduce manipulation of Google Play’s discovery systems. This will enable only credible apps to be recommended to users instead of inferior apps.
Commenting on the development, Kazushi Nagayama, Search Quality Analyst disclosed that these attempts not only violate the Google Play Developer Policy but also harm our community of developers. This is being done by hindering their chances of being discovered or recommended through our systems.
New filtering system eliminates fake reviews
The new detection and filtering systems have been designed to automatically detect and filter manipulation attempts. This includes fraudulent installations, fake reviews, and incentivised ratings.
In a joint statement with Andrew Ahn, Product Manager, Nagayama revealed that the end users are at great risk of making wrong decisions based on the inaccurate and unauthentic information.
Meanwhile, Google also stated that developers continue to upload apps, which largely exhibit fraud. These activities violate not only Google Play Developer Policy but also the very existence of Google Play. Google will immediately delete all apps which violet the guidelines outlined by them.
Even though detection of a fake installation is comparatively simple, it is very difficult to block fake reviews and incentivised ratings. Sometimes, companies ask users to install and write positive reviews in return for gifts. It’s difficult to track these activities because the review looks like original with incentives on the background.