Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Finding unusual review patterns using unexpected rules
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Extracting usability and user experience information from online user reviews
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Retrieving and analyzing mobile apps feature requests from online reviews
Proceedings of the 10th Working Conference on Mining Software Repositories
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In this paper, we explore the content of online reviews of mobile applications to get a better understanding of the most recurring issues users report through reviews, and the way the price and the rating of an app influences the type and the amount of feedback users report. Results show that users tend to provide positive feedback, often associating it with requirements for additional features. Also, users tend to provide more feedback for the lower rated apps and the optimal price range was found to be between £2.25 and £3.50.