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Review, 2 pages (450 words)

Good brief summary article review example

Article review-2

Article reference
Chen, Xu, Zhou, Zhu. “ Is this app safe for children? A comparison study of maturity ratings on Android and iOS Applications ”. International World Wide Web Steering committee. 17 May 2013. 201-207. Print.

Introduction (Objectives and article domain)

The article is solely based on growing concern of parents across the world regarding the maturity ratings of android and iOS apps. As per prevailing trends the apps are normally mandated to disclose the age rating but owing to the nudity, gore and violence dominance in current day apps, the authenticity of these agr group ratings has been dubious (Chen, Xu, Zhou, Zhu 203). This is also ratified that till date the maturity rating system for Android and iOS apps has not been rigorously reviewed by any regulatory body. The authors are in pursuit to unravel the various possible reasons for incorrect ratings and a mode of verifying the existing ratings.
The article ranges across developing an algorithm to map the app contents with corresponding user reviews, thereby developing a conclusion over the accuracy of awarded ratings to specific apps (Haradwar, “ The magic moment: Smartphone now half of all U. S. mobiles”). The mutual comparison between iOS and android ratings is also to be carried out in terms of their misclassifications causing imperfect ratings. Finally, what factors can be manipulated and regulated to control the consequent ratings, is also sought by authors.

The final rating of iOS system is clubbed into four age classifications of 4+, 9+, 12+ and 17+ (Chen, Xu, Zhou, Zhu 206). The android ratings corresponding to these ratings are Everyone, Low maturity, medium maturity and High maturity (Chen, Xu, Zhou, Zhu 206). The key differences in similar nature of apps ratings in both the above OS are then evaluated to gather the results.

Results & Conclusion

The text mining based algorithm developed, referred as ALM, meant for automated labelling of maturity ratings and the base for this algorithm is developed from those used in iOS. The algorithm, when applied in case of Android ratings , came up with a conclusion that almost 30% of android apps were overrated in maturity ratings while almost 10% were underrated in their maturity ratings (Rasmussen, “ Unreliable ratings on mobile apps”). Hence the rationale behind relative development of an algorithm to work out the maturity rating level has worked in a definite way to judge the misclassified apps in Android app system.

Works Cited

Chen, Xu, Zhou, Zhu. “ Is this app safe for children? A comparison study of maturity ratings on Android and iOS Applications ”. International World Wide Web Steering committee. 17 May 2013. 201-207. Print.
Haradwar, D. “ The magic moment: Smartphones now half of all U. S. mobiles”. Venture Beat. 29 March 2012. Accessed online http://venturebeat. com/2012/03/29/the-magic-moment-smartphones-now-half-of-all-u-s-mobiles/
Rasmussen, R. “ Unreliable ratings on mobile apps”. Kids and media. Accessed online http://kidsandmedia. org/unreliable-ratings-on-mobile-apps/

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