Data and methodology: "Mobile Augmented Reality Apps in Education: Exploring the User Experience through Large-Scale Public Reviews"
Description
This dataset is associated with the article "Mobile Augmented Reality Apps in Education: Exploring the User Experience through Large-Scale Public Reviews". It contains a static collection of all the scripts needed to reproduce the methodology of the paper (methodology folder) and the results obtained and reported in the paper (results folder). The latter include the metadata of all applications scraped, the complete information of the reviews, the results after classification, the file containing the manual classification, and the IRR test. Along with the methodology, the next 3 external references were used, all the files used are linked in this repository and refereed in the corresponding step. 1. Google-Play Scraper: Olano, F. (2020). Google-Play Scraper, version 7.1.2. Retrieved from https://github.com/facundoolano/google-play-scraper#search 2. google-play-scraper: Jo, M. (2020). google-play-scraper, version 0.0.2.2. Retrieved from https://github.com/JoMingyu/google-play-scraper. 3. AR doc tool: Panichella, S., Di Sorbo, A., Guzman, E., Visaggio, C. A., Canfora, G., & Gall, H. C. (2016). ARdoc: app reviews development-oriented classifier. Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2016, (November), 1023–1027. https://doi.org/10.1145/2950290.2983938.