Mining and Comparing User Reviews across Similar Mobile Apps

被引:6
|
作者
Su, Yanqi [1 ]
Wang, Yongchao [1 ]
Yang, Wenhua [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Comp Sci & Technol, Nanjing, Peoples R China
关键词
User review; Mobile app; Release Planning;
D O I
10.1109/MSN48538.2019.00070
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
With the rapid development of the market for mobile apps, there are a number of apps with similar functions. To gain an advantage in such a competitive environment, developers need to understand not only the strengths and weaknesses of their app but also competitive apps. User reviews contain valuable information for comparing similar apps from user preference. In this paper, we propose UISAT (User-review mining via topic Identification, Sentiment Analysis and Topic matching across apps), an automated approach to compare user reviews from similar apps with the goal of mining user feedback from competitive apps by (i) extracting the hidden topics from large volumes of user reviews using topic modeling, (ii) combining a rule-based model, user rating and user-helpful for sentiment analysis of topics and (iii) matching relevant topics across apps. Empirical studies demonstrate that UISAT is effective and promising for developers to build and maintain a more competitive app.
引用
收藏
页码:338 / 342
页数:5
相关论文
共 50 条
  • [41] Frameworks for Exploring the User Experience of Mobile Apps
    Liu, Tien-ping
    Wu, Xiao-yun
    Sun, Pei
    Wang, Hsueh-wu
    2016 INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY, ENVIRONMENT AND INFORMATION ENGINEERING (SEEIE 2016), 2016, : 307 - 312
  • [42] Analysis and Reviews on Tourism and Travel Mobile Apps of China
    Jia, Zhiyang
    Li, Ding
    He, Fengzhen
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ELECTRONICS, MECHANICS, CULTURE AND MEDICINE, 2016, 45 : 62 - 66
  • [43] USER PERCEPTIONS OF MOBILE APPS FOR PHYSICAL ACTIVITY
    Davis, Ashlee
    Ellis, Rebecca
    ANNALS OF BEHAVIORAL MEDICINE, 2019, 53 : S808 - S808
  • [44] Comparing mobile apps by identifying 'Hot' features
    Malik, Haroon
    Shakshuki, Elhadi M.
    Yoo, Wook-Sung
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2020, 107 : 659 - 669
  • [45] On Mining Mobile Apps Usage Behavior for Predicting Apps Usage in Smartphones
    Liao, Zhung-Xun
    Pan, Yi-Chin
    Peng, Wen-Chih
    Lei, Po-Ruey
    PROCEEDINGS OF THE 22ND ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM'13), 2013, : 609 - 618
  • [46] Mining Collective Opinions for Comparison of Mobile Apps
    Malika, Haroon
    Shakshuki, Elhadi M.
    11TH INTERNATIONAL CONFERENCE ON FUTURE NETWORKS AND COMMUNICATIONS (FNC 2016) / THE 13TH INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS AND PERVASIVE COMPUTING (MOBISPC 2016) / AFFILIATED WORKSHOPS, 2016, 94 : 168 - 175
  • [47] Health Tracking via Mobile Apps for Depression Self-management: Qualitative Content Analysis of User Reviews
    Polhemus, Ashley
    Simblett, Sara
    Dawe-Lane, Erin
    Gilpin, Gina
    Elliott, Benjamin
    Jilka, Sagar
    Novak, Jan
    Nica, Raluca Ileana
    Temesi, Gergely
    Wykes, Til
    JMIR HUMAN FACTORS, 2022, 9 (04):
  • [48] Mobile Augmented Reality Apps in Education: Exploring the User Experience Through Large-Scale Public Reviews
    Alfaro, Jessica Lizeth Dominguez
    Van Puyvelde, Peter
    AUGMENTED REALITY, VIRTUAL REALITY, AND COMPUTER GRAPHICS, 2021, 12980 : 428 - 450
  • [49] An Overview of Chatbot-Based Mobile Mental Health Apps: Insights From App Description and User Reviews
    Haque, M. D. Romael
    Rubya, Sabirat
    JMIR MHEALTH AND UHEALTH, 2023, 11
  • [50] Mobile health apps: An exploration of user-generated reviews in Google Play Store on a physical activity application
    Al-Abbadey, Miznah
    Fong, Megan M-W
    Wilde, Laura J.
    Ingham, Roger
    Ghio, Daniela
    DIGITAL HEALTH, 2021, 7