Exploiting Usage to Predict Instantaneous App Popularity

A large amount and different types of mobile applications (or apps) are being offered to end users via app markets. Existing mobile app recommender systems generally recommend the most popular mobile apps to mobile users to facilitate the proper selection of mobile apps. However, these apps normally generate network traffic, which will consume the user's mobile data plan and may even cause potential security issues. Therefore, more and more mobile users are hesitant or even reluctant to use the mobile apps that are recommended by the mobile app markets. To fill this crucial gap, this paper proposes a mobile app recommendation approach which can provide app recommendations by considering both the apps' popularity and their traffic cost. To achieve this goal, this paper first estimates app network traffic score based on bipartite graph. Then, this paper proposes a flexible approach based on benefit-cost analysis, which can recommend apps by maintaining a balance between the apps' popularity and the traffic cost concern. Finally, this paper evaluates our approach with extensive experiments on a large-scale data set collected from Google Play. The experimental results clearly validate the effectiveness and efficiency of our approach.

Among several traditional and novel mobile app recommender techniques that utilize a diverse set of app-related features (such as an app’s Twitter followers, various version instances, etc.), which app-related features are the most important indicators for app recommendation? In this paper, we develop a hybrid app recommender framework that integrates a variety of app-related features and recommendation techniques, and then identify the most important indicators for the app recommendation task. Our results reveal an interesting correlation with data from third-party app analytics companies; and suggest that, in the context of mobile app recommendation, more focus could be placed in user and trend analysis via social networks.

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Purpose: This study aims to understand the impact of user reviews and ratings on mobile app download intention and the moderating impact of perceived usefulness on the strength of this relationship. Design/methodology/approach: A scenario-based survey method was selected following the positivism research paradigm. For this purpose, 304 responses were collected using different versions of the same scenario. Findings: The statistical results show that 37.5% of Sri Lankan consumers' mobile app download intention is explained by mobile app ratings and reviews, which have been found to be a significant influencing factor in potential users' intentions to download the app. However, perceived usefulness does not significantly moderate this relationship. Originality: This study is the first attempt to understand the impact of user reviews and ratings on mobile app download intention in the Sri Lankan context. Implications: The findings encourage Sri Lankan mobile app developers and owners to closely monitor and respond to user reviews and ratings to better meet user expectations and improve app ratings.

Logging is a common practice in software engineering. Prior research has investigated the characteristics of logging practices in system software (e.g., web servers or databases) as well as desktop applications. However, despite the popularity of mobile apps, little is known about their logging practices. In this paper, we sought to study logging practices in mobile apps. In particular, we conduct a case study on 1,444 open source Android apps in the F-Droid repository. Through a quantitative study, we find that although mobile app logging is less pervasive than server and desktop applications, logging is leveraged in almost all studied apps. However, we find that there exist considerable differences between the logging practices of mobile apps and the logging practices in server and desktop applications observed by prior studies. In order to further understand such differences, we conduct a firehouse email interview and a qualitative annotation on the rationale of using logs in mobile app development. By comparing the logging level of each logging statement with developers’ rationale of using the logs, we find that all too often (35.4%), the chosen logging level and the rationale are inconsistent. Such inconsistency may prevent the useful runtime information to be recorded or may generate unnecessary logs that may cause performance overhead. Finally, to understand the magnitude of such performance overhead, we conduct a performance evaluation between generating all the logs and not generating any logs in eight mobile apps. In general, we observe a statistically significant performance overhead based on various performance metrics (response time, CPU and battery consumption). In addition, we find that if the performance overhead of logging is significantly observed in an app, disabling the unnecessary logs indeed provides a statistically significant performance improvement. Our results show the need for a systematic guidance and automated tool support to assist in mobile logging practices.

Is There an App for That? A Review of Popular Apps for Depression, Anxiety, and Well-Being

Background. Mobile medical software applications (apps) are used for clinical decision-making at the point of care. Objectives. To determine (1) the usage, reliability, and popularity of mobile medical apps and (2) medical students' perceptions of app usage effect on the quality of patient-provider interaction in healthcare settings. Methods. An anonymous web-based survey was distributed to medical students. Frequency of use, type of app used, and perceptions of reliability were assessed via univariate analysis. Results. Seven hundred thirty-one medical students responded, equating to a response rate of 29%. The majority (90%) of participants thought that medical apps enhance clinical knowledge, and 61% said that medical apps are as reliable as textbooks. While students thought that medical apps save time, improve the care of their patients, and improve diagnostic accuracy, 53% of participants believed that mobile device use in front of colleagues and patients makes one appear less competent. Conclusion. While medical students believe in the utility and reliability of medical apps, they were hesitant to use them out of fear of appearing less engaged. Higher levels of training correlated with a greater degree of comfort when using medical apps in front of patients.

This research adopted the unified theory of acceptance and use of technology (UTAUT) to emphasize the use of the PX Pay mobile payment app for PX Mart, the most popular supermarket in Taiwan, and examine the degree of involvement as a moderator. The influence of factors related to PX Mart’s target customer groups on their shopping intentions and usage behaviors were discussed, with subsequent benefits and optimization directions. This study indicated the following results. First, performance expectations, ease-of-use expectations, and social impact enhance consumers’ behavioral intention and behavioral intention significantly influence usage behavior. Second, gender has no significant moderating effect on the proposed model. Third, age has a moderating effect from performance expectations and ease-of-use expectations, social influence on behavioral intention. Fourth, use is more significantly affected by perceived stakeholders for customers over age 50 than for those age 30–39. Fifth, the degree of involvement significantly affects the relationship between behavioral intention and usage behavior in terms of social influence and facilitating conditions effects. Finally, we provided academic and practical implications and make contributions to both the online payment industry and academia.

BackgroundPersistent smoking after a cancer diagnosis predicts worse treatment outcomes and mortality, but access to effective smoking cessation interventions is limited. Smartphone apps can address this problem by providing a highly accessible, low-cost smoking cessation intervention designed for patients with a recent cancer diagnosis.ObjectiveThis study aimed to summarize our development process and report the trial design, feasibility, participant acceptability, preliminary effectiveness, and impact on processes of change (eg, cancer stigma) of the first-known smoking cessation smartphone app targeted for cancer patients.MethodsWe used an agile, user-centered design framework to develop a fully automated smartphone app called Quit2Heal that provided skills training and stories from cancer survivors focusing on coping with internalized shame, cancer stigma, depression, and anxiety as core triggers of smoking. Quit2Heal was compared with the National Cancer Institute’s QuitGuide, a widely used stop smoking app for the general population, in a pilot double-blinded randomized trial with a 2-month follow-up period. Participants were 59 adult smokers diagnosed with cancer within the past 12 months and recruited through 2 cancer center care networks and social media over a 12-month period. The most common types of cancer diagnosed were lung (21/59, 36%) and breast (10/59, 17%) cancers. The 2-month follow-up survey retention rate was 92% (54/59) and did not differ by study arm (P=.15).ResultsCompared with QuitGuide participants, Quit2Heal participants were more satisfied with their assigned app (90% [19/21] for Quit2Heal vs 65% [17/26] for QuitGuide; P=.047) and were more likely to report that the app assigned to them was made for someone like them (86% [18/21] for Quit2Heal vs 62% [16/26] for QuitGuide; P=.04). Quit2Heal participants opened their app a greater number of times during the 2-month trial period, although this difference was not statistically significant (mean 10.0, SD 14.40 for Quit2Heal vs mean 6.1, SD 5.3 for QuitGuide; P=.33). Self-reported 30-day point prevalence quit rates at the 2-month follow-up were 20% (5/25) for Quit2Heal versus 7% (2/29) for QuitGuide (odds ratio 5.16, 95% CI 0.71-37.29; P=.10). Quit2Heal participants also showed greater improvement in internalized shame, cancer stigma, depression, and anxiety, although these were not statistically significant (all P>.05).ConclusionsIn a pilot randomized trial with a high short-term retention rate, Quit2Heal showed promising acceptability and effectiveness for helping cancer patients stop smoking. Testing in a full-scale randomized controlled trial with a longer follow-up period and a larger sample size is required to test the effectiveness, mediators, and moderators of this promising digital cessation intervention.Trial RegistrationClinicalTrials.gov NCT03600038; https://clinicaltrials.gov/ct2/show/NCT03600038

Cholinergic stimulation of the caudate nucleus in rats: A model of Parkinson's disease

Despite continuous efforts to build and update mobile network infrastructure, mobile devices in developing regions continue to be constrained by limited bandwidth. Unfortunately, this coincides with a period of unprecedented growth in the sizes of mobile applications. Thus it is becoming prohibitively expensive for users in developing regions to download and update mobile apps critical to their economic and educational development. Unchecked, these trends can further contribute to a large and growing global digital divide. Our goal is to better understand the source of this rapid growth in mobile app code size, whether it is reflective of new functionality, and identify steps that can be taken to make existing mobile apps more friendly to bandwidth constrained mobile networks. We hypothesize that much of this growth in mobile apps is due to poor resource/code management, and do not reflect proportional increases in functionality. Our hypothesis is partially validated by mini-programs, apps with extremely small footprints gaining popularity in Chinese mobile platforms. Here, we use functionally equivalent pairs of mini-programs and Android apps to identify potential sources of “bloat,” i.e., inefficient uses of code or resources that contribute to large package sizes. We analyze a large sample of popular Android apps and quantify instances of code and resource bloat. We develop techniques for automated code and resource trimming, and successfully validate them on a large set of Android apps. We hope our results will lead to continued efforts to streamline mobile apps, making them easier to access and maintain for users in developing regions.

Uncovering top-ranking factors for mobile apps through a multimethod approach

Mobile application developers have started to realize that quality plays a vital role in increasing the popularity of mobile applications (apps), thereby directly influencing economical profit (in-app purchases revenue) and app-related success factors (i.e., number of downloads). Therefore, developers have become increasingly concerned with taking preemptive actions to ensure the quality of their apps. In general, developers have been relying on testing as their main quality assurance practice. However, little is known about how much mobile app testing contributes to increasing user level satisfaction. In this paper we investigate to what extent testing mobile apps contributes to achieving higher user satisfaction. To this end, we probed into whether there is a relation between having automated tests and overall user satisfaction. We looked into users ratings, which express their level of satisfaction with apps, and users reviews, which often include bug (i.e., fault) reports. By analyzing a quantitative indicator of user satisfaction (i.e., user rating), we found that there is no significant difference between apps with automated tests and apps that have been developed without test suites. We also applied sentiment analysis on user reviews to examine the main differences between apps with and without test suites. The results of our review-based sentiment analysis suggest that most apps with and without test suites score quite high for user satisfaction. In addition, we found that update-related problems are far more common in apps with test suites, while apps without test suites are likely to have battery-drain problems.

BackgroundType 2 diabetes (T2DM) is highly prevalent in China, affecting over 114 million people. While mHealth interventions have shown promise, there is limited research on T2DM management apps in real-world app stores. ObjectiveThis study aimed to systematically search and analyze T2DM care mobile apps in the Chinese market, describing their features, and functions, and evaluating the quality of the most popular apps using validated tools. MethodsWe conducted a comprehensive search in Chinese Android and iOS app stores for T2DM management apps. We downloaded 138 eligible ones for a general review of their key features and function. We also assessed the quality of the top 20 apps from both platforms using the Mobile App Rating Scale (MARS) by both researcher and patient. ResultsA total of 3524 apps were searched. 138 eligible apps were downloaded for general review and 29 popular apps were included for quality assessment. Most apps were designed for patient users (87.0 %) and developed by commercial companies (85.5 %). Common functions included blood glucose monitoring, diabetes education, integration with measuring devices, medication adherence reminders, teleconsultation services, and diabetes risk factor tracking. The researcher's evaluation yielded an average MARS score of 4.0 out of 5 for popular apps, with subscale scores of functionalities (4.5), aesthetics (4.1), engagement (3.7), and information (3.6). However, patient ratings were lower in functionality (3.5), aesthetics (3.4), and engagement (2.6), and the patient faced difficulties with information-related items. Similar trends were observed in subject quality items. ConclusionApp developers should engage caregivers, and family members as target users, and involve government agencies as partners to improve T2DM management apps. Future apps should incorporate scientifically proven advanced functions to enhance their effectiveness. The quality assessment highlighted weaknesses in engagement and information and the importance of user-centric approaches in app development.

Attention Deficit Hyperactivity Disorder (ADHD) experts and individuals with ADHD have made many recommendations concerning mobile apps that could potentially help college students succeed. But do students know about these recommended apps? Do they find them useful? How do students use mobile apps for completing schoolwork? To answer these questions we carried out two empirical studies. In study 1, 35 Canadian postsecondary students who self-reported ADHD and 74 students without disabilities completed an online LimeSurvey questionnaire and indicated which of 20 expert recommended schoolwork-related apps they had tried and which they liked. In Study 2, nine students with ADHD specified how they used their technologies to complete schoolwork. Results indicate that students with and without ADHD were familiar with only 13 of the 20 apps recommended by experts, and that they liked only 11. For completing academic work, the most popular apps were built-in smartphone camera and recording apps. Students also found Microsoft, Google, Pomodoro and Kahoot apps helpful. Discord was the most popular app for collaboration with classmates. Results show that students with and without ADHD found the same apps and technologies helpful. To the best of our knowledge this is the first study to actually query students with ADHD about their app use and preferences. We conclude that disability service providers, academic administrators and access technologists need to stay up-to-date about general use mobile apps to enable them to make appropriate recommendations to help students with ADHD succeed in college.