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Revisitation analysis of smartphone app use

Simon L. Jones, Denzil Ferreira, Simo Hosio, Jorge Goncalves, Vassilis Kostakos
2015 Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '15  
We present a revisitation analysis of smartphone use to investigate the question: do smartphones induce usage habits?  ...  We analysed three months of application launch logs from 165 users in naturalistic settings.  ...  s [3] large-scale study on mobile application usage revealed that mobile phone owners use their device for an average of 59 minutes daily, with the average application session lasting 72 seconds.  ... 
doi:10.1145/2750858.2807542 dblp:conf/huc/JonesFHGK15 fatcat:ycncfo36t5hgrbjp5v6upxatpy

FraudDroid: Automated Ad Fraud Detection for Android Apps [article]

Feng Dong, Haoyu Wang, Li Li, Yao Guo, Tegawende F. Bissyande, Tianming Liu, Guoai Xu, Jacques Klein
2018 arXiv   pre-print
We then propose, FraudDroid, a novel hybrid approach to detect ad frauds in mobile Android apps.  ...  In this work, we investigate a wide range of mobile ad frauds to provide a comprehensive taxonomy to the research community.  ...  Nevertheless, since exhaustively exercising an app is time-consuming, the analysis cannot scale to market sizes.  ... 
arXiv:1709.01213v4 fatcat:pjbywoikenel7doaoyouquu73a

Apps, Places and People: strategies, limitations and trade-offs in the physical and digital worlds [article]

Marco De Nadai, Angelo Cardoso, Antonio Lima, Bruno Lepri, Nuria Oliver
2019 arXiv   pre-print
We address this question through the analysis of pseudonymised mobility and mobile application (app) usage data of 400,000 individuals in a European country for six months.  ...  Our empirical findings provide an intriguing picture linking human behaviour in the physical and digital worlds which bridges research studies from Computer Science, Social Physics and Computational Social  ...  We have compared the statistical properties of app usage and mobility through the analysis of a large data set containing the mobile app behaviour of hundreds of thousands of individuals over six months  ... 
arXiv:1904.09350v1 fatcat:5zswr6rhhfekjczhadbboe2zsa

Smartphone App Usage Prediction Using Points of Interest

Donghan Yu, Yong Li, Fengli Xu, Pengyu Zhang, Vassilis Kostakos
2018 Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies  
In this paper we present the first population-level, city-scale analysis of application usage on smartphones.  ...  We present the first population-level, city-scale analysis of application usage on smartphones.  ...  CONCLUSION In this paper, we design, to the best of our knowledge, the first system to predict the Location-level app usage from the POI via a large-scale mobile data accessing records.  ... 
doi:10.1145/3161413 fatcat:6bofzlhfsnfhrp7ag5ulmdabwe

Enhancing Mobile App User Understanding and Marketing with Heterogeneous Crowdsourced Data: A Review

Bin Guo, Yi Ouyang, Tong Guo, Longbing Cao, Zhiwen Yu
2019 IEEE Access  
The mobile app market has been surging in recent years. It has some key differentiating characteristics which make it different from traditional markets.  ...  This paper reviews CrowdApp, a research field that leverages heterogeneous crowdsourced data for mobile app user understanding and marketing.  ...  As a new type of business, the empirical economic models can be applied for app data analysis.  ... 
doi:10.1109/access.2019.2918325 fatcat:de763kc4qbdy5ijo55jxyhzgt4

Smartphone App Usage Prediction Using Points of Interest [article]

Donghan Yu, Yong Li, Fengli Xu, Pengyu Zhang, Vassilis Kostakos
2017 arXiv   pre-print
In this paper we present the first population-level, city-scale analysis of application usage on smartphones.  ...  We demonstrate that our technique has an 83.0% hitrate in successfully identifying the top five popular applications, and a 0.15 RMSE when estimating usage with just 10% sampled sparse data.  ...  CONCLUSION In this paper we present, to the best of our knowledge, the rst system to predict the Location-level app usage from the POI via a large-scale mobile data accessing records.  ... 
arXiv:1711.09337v1 fatcat:xxypeyfj7jfghevjjruurzftmm

FraudDroid: automated ad fraud detection for Android apps

Feng Dong, Haoyu Wang, Li Li, Yao Guo, Tegawendé F. Bissyandé, Tianming Liu, Guoai Xu, Jacques Klein
2018 Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering - ESEC/FSE 2018  
We then propose, FraudDroid, a novel hybrid approach to detect ad frauds in mobile Android apps.  ...  In this work, we investigate a wide range of mobile ad frauds to provide a comprehensive taxonomy to the research community.  ...  Nevertheless, since exhaustively exercising an app is time-consuming, the analysis cannot scale to market sizes.  ... 
doi:10.1145/3236024.3236045 dblp:conf/sigsoft/DongWLGBLXK18 fatcat:seu676kfefcvfky34k7wkzoto4

Mining Device-Specific Apps Usage Patterns from Large-Scale Android Users [article]

Huoran Li, Xuan Lu
2017 arXiv   pre-print
To approach this question, we collect a longitudinal data set of app usage through a leading Android app store in China, called Wandoujia.  ...  We present a comprehensive study on investigating how the choices of device models affect user behaviors such as the adoption of app stores, app selection and abandonment, data plan usage, online time  ...  Based on such a large-scale data set, we explore a comprehensive study on how the device models can impact the app usage. • We find significant correlations between the choice of device models and app  ... 
arXiv:1707.09252v1 fatcat:v2z3yb2rwvaunfw3v4fttrpfwq

App-based Delivery of Clinical Emotional Freedom Techniques Reduces Anxiety and Stress: Cross-sectional Study of App User Self-Ratings (Preprint)

Dawson Church, Peta Stapleton, Debbie Sabot
2020 JMIR mHealth and uHealth  
This study assessed the effect of a mHealth app on user self-ratings of psychological distress in a sample of 270,461 app users.  ...  The burgeoning area of mobile health (mHealth) has experienced rapid growth in mobile applications (apps) designed to address mental health issues.  ...  The authors disclose receipt of the following financial support for the research, authorship, and/or publication of this paper: data analysis was made possible by donations from individuals to the National  ... 
doi:10.2196/18545 pmid:32862128 fatcat:u6bqac3bffbtjd24plryyycoea

App Usage Predicts Cognitive Ability in Older Adults

Mitchell L. Gordon, Leon Gatys, Carlos Guestrin, Jeffrey P. Bigham, Andrew Trister, Kayur Patel
2019 Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19  
While older adults differ from younger adults in app usage behavior, the "cognitively young" older adults use smartphones much like their younger counterparts.  ...  To characterize smartphone usage among older adults, we collected iPhone usage data from 84 healthy older adults over three months.  ...  on surveys of older adults and their preferences, rather than analysis of their actual app usage data.  ... 
doi:10.1145/3290605.3300398 dblp:conf/chi/GordonGGBTP19 fatcat:gevchaguazdbtkncrax2kipq2i

A contextual collaborative approach for app usage forecasting

Yingzi Wang, Nicholas Jing Yuan, Yu Sun, Fuzheng Zhang, Xing Xie, Qi Liu, Enhong Chen
2016 Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '16  
We evaluate the model on a large real-world app usage dataset, which validates that CCF outperforms state-of-the-art methods in terms of both accuracy and efficiency for long-term app usage forecasting  ...  In this paper, we propose a contextual collaborative forecasting (CCF) model to address the above issues.  ...  Besides, these apps have evident usage peak at 8am-4pm during workdays, which is consistent of our empirical thoughts of work time during a day.  ... 
doi:10.1145/2971648.2971729 dblp:conf/huc/WangYSZXLC16 fatcat:2v46rcz2sne5jd6p5jezn7agz4

Empirically assessing opportunities for prefetching and caching in mobile apps

Yixue Zhao, Paul Wat, Marcelo Schmitt Laser, Nenad Medvidović
2018 Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering - ASE 2018  
Network latency in mobile software has a large impact on user experience, with potentially severe economic consequences.  ...  We find that there is a substantial opportunity to leverage prefetching and caching in mobile apps, but that suitable techniques must take into account the nature of apps' network interactions and idiosyncrasies  ...  Halfond, Jiaping Gui, and the rest of their research group at the University of Southern California for providing us with the APKs for our subject apps. This work is supported by the U.S.  ... 
doi:10.1145/3238147.3238215 dblp:conf/kbse/ZhaoWLM18 fatcat:74ylg62eprc2tjqkq3b6tdviru

Fast app launching for mobile devices using predictive user context

Tingxin Yan, David Chu, Deepak Ganesan, Aman Kansal, Jie Liu
2012 Proceedings of the 10th international conference on Mobile systems, applications, and services - MobiSys '12  
Unfortunately, even the basic primitive of launching a mobile app is sorrowfully sluggish: 20 seconds of delay is not uncommon even for very popular apps.  ...  FALCON uses novel features derived through extensive data analysis, and a novel cost-benefit learning algorithm that has strong predictive performance and low runtime overhead.  ...  ACKNOWLEDGEMENTS We extend our thanks to Lin Zhong, Ahmad Rahmati, Clayton Shepard, and the Rice LiveLab team for making available their extensive mobile user study dataset.  ... 
doi:10.1145/2307636.2307648 dblp:conf/mobisys/YanCGKL12 fatcat:7p5lfl5rtzfp5oaqbrn3au27zm

What Do People Complain About Drone Apps? A Large-Scale Empirical Study of Google Play Store Reviews

Kanimozhi Kalaichelavan, Haroon Malik, Narman Husnu, Sreehari Sreenath
2020 Procedia Computer Science  
Towards this end, a large-scale empirical study of UAV or drone-related apps of Google Play Store Platform is conducted.  ...  Towards this end, a large-scale empirical study of UAV or drone-related apps of Google Play Store Platform is conducted.  ...  This paper proposes to study a large number of drone apps from the Google Play Store.  ... 
doi:10.1016/j.procs.2020.03.124 fatcat:ubu52ctxrjei3bb7lz2uea5ivu

Automated Test Selection for Android Apps Based on App Domain

Luca Ardito, Riccardo Coppola, Simone Leonardi, Maurizio Morisio, Ugo Buy
2020 IEEE Access  
the main section of the app, very common in news, music and audio apps. • List: This class contains activities consisting of a dynamically-populated list of interactive elements, typically implemented  ...  It is evident that we might have an important semantic core in the strings.xml file since the strings correspond to the main functionality of the app.  ...  His interests are in the general area of software engineering with emphasis on modeling and analysis of concurrent and real-time systems.  ... 
doi:10.1109/access.2020.3029735 fatcat:dqqcwzrzfzcrxhdr54bjb2vycu
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