{"title":"App Competition Matters: How to Identify Your Competitor Apps?","authors":"Md. Kafil Uddin, Qiang He, Jun Han, C. Chua","doi":"10.1109/SCC49832.2020.00055","DOIUrl":null,"url":null,"abstract":"App stores, such as Google Play and Apple Store, contain abundance of information, including descriptions and reviews of various apps. They provide valuable information for app developers to learn about their own apps as well as similar apps for improving their apps, e.g., adding popular features or removing unpopular features. A place to start this learning process is to identify the competitor apps of a given target app in terms of their features, popularity as well as other relevant aspects. Given the large number of apps and the large amount of information available about these apps, it is a very challenging task for app developers to effectively and efficiently identify competitor apps. In this paper, we introduce a novel approach for identifying the competitor apps of a given target app, which includes three major components. Firstly, we identify the factors that characterise the competition between apps. Then, based on the identified competition factors, we extract and process the relevant information from the app store about the target app and the apps in the same app category. Finally, we cluster the apps based on their similarity across all the competition factors and identify those apps that are in the same cluster as the target app as its competitor apps. We evaluate our approach by comparing its results with corresponding search results in (1) Google Trends and (2) Google Search. The results show that our approach is effective in identifying competitor apps.","PeriodicalId":274909,"journal":{"name":"2020 IEEE International Conference on Services Computing (SCC)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Services Computing (SCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCC49832.2020.00055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
App stores, such as Google Play and Apple Store, contain abundance of information, including descriptions and reviews of various apps. They provide valuable information for app developers to learn about their own apps as well as similar apps for improving their apps, e.g., adding popular features or removing unpopular features. A place to start this learning process is to identify the competitor apps of a given target app in terms of their features, popularity as well as other relevant aspects. Given the large number of apps and the large amount of information available about these apps, it is a very challenging task for app developers to effectively and efficiently identify competitor apps. In this paper, we introduce a novel approach for identifying the competitor apps of a given target app, which includes three major components. Firstly, we identify the factors that characterise the competition between apps. Then, based on the identified competition factors, we extract and process the relevant information from the app store about the target app and the apps in the same app category. Finally, we cluster the apps based on their similarity across all the competition factors and identify those apps that are in the same cluster as the target app as its competitor apps. We evaluate our approach by comparing its results with corresponding search results in (1) Google Trends and (2) Google Search. The results show that our approach is effective in identifying competitor apps.