NChecker

Net neutrality or “Open Internet” rulemaking has been ongoing for more than a decade. Some 50 nations have adopted formal rules including the US (then repealed), the European Union, India, and many countries in Latin America. Among other arguments, it is asserted that net neutrality rules are necessary for application innovation. While the focus for policymakers has largely been to make rules, there is less attention on how to measure the impact of such rules and how well they achieve their innovation goals. The article summaries a specific research investigation to what degree the introduction of rules in a given country stimulates innovation in that country’s mobile app ecosystem. The focus in on mobile networks because it allowed the most consistent data across countries. The study covered 53 countries, their net neutrality policies (or lack thereof), and the results to the respective mobile application ecosystems of the countries adopting rules between the period of 2010–2016. This investigation tests the proposition that countries which adopt net neutrality rules should experience an increase in mobile app development innovation within their national economy. To test this, a statistical methodology was developed based upon measuring the number of locally developed mobile apps in the country for relevant periods before and after rules are imposed and the corresponding app downloads, usage, and revenue. Measurement was conducted with two independent toolsets and adjusted for the sophistication and penetration of advanced mobile networks in the country. To make more meaningful comparisons and avoid inevitable heterogeneity across the countries, the investigation focuses on two similar countries with different rules, Denmark with soft rules (self-regulation) and Netherlands with hard rules (legislation). The study reviewed the leading theories of innovation as well as the foundational papers in net neutrality to explain the observed discrepancies. The research finds significant statistical support for “soft” net neutrality measures adopted on a voluntary basis. Hard rules adopted through legislation and regulation were not associated with greater mobile app development for the given country. Denmark increased in local mobile app development while Netherlands decreased. Additionally, the explosion of mobile apps from countries with no net neutrality rules and the general dearth of mobile apps from countries which have had hard rules for years runs counter to expected results. This suggests that policymakers revisit their assumptions and expectations for net neutrality policy.

Aim/Purpose: This paper focuses on app review analysis techniques, driven by the rapid advancement of the mobile app market and NLP techniques in optimizing mobile app user experiences. Background: Owing to technological advancements, app review analysis has rapidly evolved. This study examines both conventional and emerging techniques, including current advancements such as large language models (LLMs) in app review analysis. It provides an overview of the various methods used across different categories of app review analysis, comparing effective strategies for identifying user concerns and enhancing app functionality. Methodology: A systematic review was utilized based on two major standard guidelines, PRISMA and Kitchenham’s guidelines, for the period of 2014 to 2024. After defining the review protocol, papers were identified through keyword-based searches on six major online databases: Scopus, Web of Science, IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Following screening and excluding papers based on defined quality criteria, 53 papers were considered for this study. The use of PRISMA ensures a transparent and reproducible review process, while Kitchenham’s guidelines provide a structured and rigorous approach for evaluating and synthesizing the literature. Contribution: This review study aims to evaluate the current state of knowledge on app review analysis techniques to improve mobile app user experiences. This study categorized the existing state-of-the-art papers into eight different categories, such as sentiment analysis, review classification, summarization, and prioritization, and examined challenges related to app review analysis. Furthermore, the study emphasizes the potential of LLMs for optimizing and automating app review analysis and provides future directions to address gaps in user-centric app development. Findings: Among the eight main categories defined in app review analysis, sentiment analysis is the most prevalent, followed by review classification and information extraction. Most studies use a combination of these categories to achieve a comprehensive goal. Prioritization techniques such as risk matrices, thumbs-up count-based approach, and anomaly detection are widely used to identify emerging issues. Extracting meaningful information and evaluating the proposed approach are the most common challenges identified. Novel LLMs, like Chat-GPT, significantly enhance review analysis by automating the process, improving feature extraction, and enabling context-aware review classification. Recommendations for Practitioners: The combination of conventional approaches and novel LLM-based methods can enhance both the efficiency and accuracy in identifying and addressing critical issues raised through mobile app user reviews. It effectively prioritizes user concerns by leveraging the strengths of both traditional preprocessing techniques and advanced LLMs. Recommendation for Researchers: Researchers are encouraged to explore the integration of emerging technologies like LLMs to enhance the of app review analysis, particularly in feature-specific sentiment analysis. Impact on Society: The results of this study contribute to enhancing the mobile app user experience through effective app review analysis, which improves user satisfaction and supports user-centered app development. This ultimately leads to a better mobile app ecosystem, benefiting both users and developers. Future Research: In the future, this research can be extended in multiple directions. Researchers can address the existing research gaps that LLMs have yet to address, particularly in prioritizing user concerns. Additionally, there is potential for further research on tool implementations focusing on identifying persistent issues through time series analysis by considering the app version and date of the app reviews. Moreover, there is a need to develop comprehensive frameworks that are more generalizable across different apps and categories, with a focus on identifying user concerns related to specific features.

This article describes how the mobile app market is growing day by day. Mobile app stores have created the opportunity for the users to publicly provide feedback on mobile apps that they have installed or used. In this way, users are involved in the design and development of mobile apps, which was done by designers and developers before. Online user reviews are a useful source to know the user's perception about mobile apps and thus provide a way of co-value creation. This article is conducted to investigate the factors affecting the acceptability of mobile Apps. Main purpose of this article is to use online reviews for construction of a model instead of using existing acceptance theories. The model proposed in this research is based on the analysis of reviews and app information extracted from the Google Play Store. The ratings and number of installs are two key indicators of the popularity of an app. Other characteristics like price, category and size also influence the user's selection of an app. The findings showed the appropriateness of the proposed model and hypotheses for evaluating mobile apps acceptability and popularity. This article provides mobile app developers and marketers with an insight into the mobile app popularity and acceptability dynamics.

Mobile app development within mental health is often time- and resource-consuming, challenging the development of mobile apps for psychiatry. There is a continuum of software development methods ranging from linear (waterfall model) to continuous adaption (Scrum). Rapid application development (RAD) is a model that so far has not been applied to psychiatric settings and may have some advantages over other models. This study aims to explore the utility of the RAD model in developing a mobile app for patients with borderline personality disorder (BPD) in a psychiatric outpatient setting. The 4 phases of the RAD model: (1) requirements planning, (2) user design, (3) construction, and (4) cutover, were applied to develop a mobile app within psychiatric outpatient services for patients diagnosed with BPD. For the requirements planning phase, a short time frame was selected to minimize the time between product conceptualization and access within a clinical setting. Evidenced-based interactive content already developed was provided by current staff to enhance usability and trustworthiness. For the user design phase, activity with video themes and a discrete number of functions were used to improve the app functionality and graphical user interface. For the construction phase, close collaboration between clinicians, researchers, and software developers yielded a fully functional, in-house-developed app ready to be tested in clinical practice. For the cutover phase, the mobile app was tested successfully with a small number (n=5) of patients with a BPD. The RAD model could be meaningfully applied in a psychiatric setting to develop an app for BPD within a relatively short time period from conceptualization to implementation in the clinic. Short time frames and identifying a limited number of stakeholders with relevant skills in-house facilitated the use of this model. Despite some limitations, RAD could be a useful model in the development of apps for clinical populations to enable development and access to evidence-based technology.

Background/Purpose:We are living in an era where many disruptive technologies have emerged that have changed the entire perception of the business world. One of them is the emergence of mobile application development, which has completely changed the way people use software. While in the past software development usually meant single or web applications, now there is a huge scope for mobile application development. Standalone technologies require users to have at least one personal computer to use their applications. However, since the only platform on which the application can be used is the mobile phone, the target audience for the development of this application does a lot. Mobile app development has now become a norm for services to reach their destinations faster because almost everyone has access to mobile devices. The app development industry has grown at a rapid pace since its inception. This article covers the mobile app industry and its management in India in detail. Objectives: Analyze and understand the mobile app industry globally and in India, understand the trends, usage, revenue, cost and performance of app development in India Answer and perform SWOC analysis of the mobile app industry.

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.

Mobile app development has been considered as one of the fastest growing segments of the software industry both worldwide and in Saudi Arabia. Due to their pervasiveness, mobile applications call for consideration of complex and rapidly changing requirements given the diversity of their environments. Therefore, agile is considered the most suitable methodology for developing mobile apps. However, little research has investigated agile adoption in mobile app development in the real context. Therefore, the purpose of this PhD is to investigate the factors that have a significant impact on agile adoption in mobile app development by small and medium-size software organisations in Saudi Arabia. The expected key contribution of this research will be a deep insight into agile adoption in mobile app development, and the design and development of tools and techniques that may support agile adoption within Saudi context.

Android apps must work correctly even if their execution is interrupted by external events. For instance, an app must work properly even if a phone call is received, or after its layout is redrawn because the smartphone has been rotated. Since these events may require destroying, when the execution is interrupted, and recreating, when the execution is resumed, the foreground activity of the app, the only way to prevent the loss of state information is saving and restoring it. This behavior must be explicitly implemented by app developers, who often miss to implement it properly, releasing apps affected by data loss problems, that is, apps that may lose state information when their execution is interrupted. Although several techniques can be used to automatically generate test cases for Android apps, the obtained test cases seldom include the interactions and the checks necessary to exercise and reveal data loss faults. To address this problem, this paper presents Data Loss Detector (DLD), a test case generation technique that integrates an exploration strategy, data-loss-revealing actions, and two customized oracle strategies for the detection of data loss failures. DLD has been able to reveal 75% of the faults in a benchmark of 54 Android app releases affected by 110 known data loss faults. DLD also revealed unknown data loss problems, outperforming competing approaches.

BackgroundOver the past few years, studies have increasingly focused on the development of mobile apps as complementary tools to existing traditional pharmacovigilance surveillance systems for improving and facilitating adverse drug reaction (ADR) reporting.ObjectiveIn this research, we evaluated the potentiality of a new mobile app (vaxEffect@UniMiB) to perform longitudinal studies, while preserving the anonymity of the respondents. We applied the app to monitor the ADRs during the COVID-19 vaccination campaign in a sample of the Italian population.MethodsWe administered vaxEffect@UniMiB to a convenience sample of academic subjects vaccinated at the Milano-Bicocca University hub for COVID-19 during the Italian national vaccination campaign. vaxEffect@UniMiB was developed for both Android and iOS devices. The mobile app asks users to send their medical history and, upon every vaccine administration, their vaccination data and the ADRs that occurred within 7 days postvaccination, making it possible to follow the ADR dynamics for each respondent. The app sends data over the web to an application server. The server, along with receiving all user data, saves the data in a SQL database server and reminds patients to submit vaccine and ADR data by push notifications sent to the mobile app through Firebase Cloud Messaging (FCM). On initial startup of the app, a unique user identifier (UUID) was generated for each respondent, so its anonymity was completely ensured, while enabling longitudinal studies.ResultsA total of 3712 people were vaccinated during the first vaccination wave. A total of 2733 (73.6%) respondents between the ages of 19 and 80 years, coming from the University of Milano-Bicocca (UniMiB) and the Politecnico of Milan (PoliMi), participated in the survey. Overall, we collected information about vaccination and ADRs to the first vaccine dose for 2226 subjects (60.0% of the first dose vaccinated), to the second dose for 1610 subjects (43.4% of the second dose vaccinated), and, in a nonsponsored fashion, to the third dose for 169 individuals (4.6%).ConclusionsvaxEffect@UniMiB was revealed to be the first attempt in performing longitudinal studies to monitor the same subject over time in terms of the reported ADRs after each vaccine administration, while guaranteeing complete anonymity of the subject. A series of aspects contributed to the positive involvement from people in using this app to report their ADRs to vaccination: ease of use, availability from multiple platforms, anonymity of all survey participants and protection of the submitted data, and the health care workers’ support.

Due to the advance of mobile technology, use of mobile devices such as smartphones has been growing rapidly in the U.S. and worldwide. Many health related mobile apps have been developed for care professionals and patients as well. However, studies indicate that there is a gap between science and commercially developed mobile apps. In addition to this, there is no framework to guide devlopment of a mobile app to overcome many challenges and obstacles. Through the development of a pain management mobile app for cancer patients, a framework was developed. A proposed framework was based on the technology acceptance model, ensuring usefulness and ease of use for end users. The first two steps in the framework enforce accurate knowledge translation and communication to build a science based mobile app. Iterative decisions points between steps enhance accomplishment of each step.

One of the biggest growth areas in e-mental health resources has been the development and use of mobile mental health apps for smartphones and tablet devices. Such apps are being downloaded at increasing rates, but there have been questions about their efficacy and the research methodologies used to examine this. A review of the major app marketplaces, the Apple App Store and Google Play store, was conducted to locate apps claiming to offer a therapeutic treatment for depression and/or anxiety, and have research evidence for their effectiveness, according to their app store descriptions. App store descriptions were also analyzed to determine whether the app had been developed with mental health expert input; whether they had been developed in association with a government body, academic institution, or medical facility; and, whether or not they were free to download. Overall, 3.41% of apps had research to justify their claims of effectiveness, with the majority of that research undertaken by those involved in the development of the app. Other results indicated that 30.38% of shortlisted apps claimed to have expert development input; 20.48% had an affiliation with a government body, academic institution, or medical facility; and, 74.06% were free to download. Future research must consider other methodologies that may facilitate more research being completed on a greater number of apps, and future development needs to incorporate greater levels of input by mental health experts. Ways in which app stores could play a key role in encouraging more scientific research into the effectiveness of the mental health apps they sell are discussed.

Given the attributes of mobile apps that shorten the time to make purchase decisions while enabling easy purchase cancellations, usability can be regarded to be a highly prioritized quality attribute among the diverse quality attributes that must be provided by mobile apps. With that backdrop, mobile app developers have been making great effort to minimize usability hampering elements that degrade the merchantability of apps in many ways. Most elements that hamper the convenience in use of mobile apps stem from those potential errors that occur when GUIs are designed. In our previous study, we have proposed a technique to analyze the usability of mobile apps using user behavior logs. We proposes a technique to detect usability hampering elements lying dormant in mobile apps` GUI models by expressing user behavior logs with finite state models, combining user behavior models extracted from multiple users, and comparing the combined user behavior model with the expected behavior model on which the designer`s intention is reflected. In addition, to reduce the burden of the repeated test operations that have been conducted by existing developers to detect usability errors, the present paper also proposes a mobile usability error detection automation tool that enables automatic application of the proposed technique. The utility of the proposed technique and tool is being discussed through comparison between the GUI issue reports presented by actual open source app developers and the symptoms detected by the proposed technique.

To assess the feasibility of a novel, partnered technology development process to co-create mobile health applications (apps) addressing community health priorities, using psychoeducation of cognitive behavioral therapy (CBT) principles for enhancing resilience as an example. Stakeholder engagement, workgroups, pilot feasibility study using mixed methods during October 2013 through January 2016 over three phases: 1) defining the vision of the project and increasing technical capacity, 2) co-development and pilot testing of the app, and 3) planning for sustainability. An academic-community partnership in South Los Angeles, California. Eight stakeholders; 30 pilot participants from the community. Qualitative analysis of audio-recordings of the app development process and stakeholder interviews, surveys of stakeholders' perception of the development process, app use data, and feedback from pilot participants. The participatory technology development process resulted in creation and pilot-testing of a resiliency-focused text messaging app. Of the 1,107 messages sent, 23 out of 30 (77%) app users responded to explore interactive content. Stakeholders reported increased perceived competency in creating mobile apps and that the process fostered a culture of co-leadership. There was also sustained engagement in mobile app development by stakeholders beyond the initial project period. This is the first study, to our knowledge, to demonstrate the feasibility of participatory technology development, an approach involving direct participation in the development, tailoring and maintenance of a mobile app by a broad set of stakeholders with high representation from racial/ethnic minorities from an under-resourced community. Participatory technology development is a promising approach for creating sustainable, relevant and engaging health technologies across different technological, clinical and community settings.

Interventions to promote health and well-being based on the construction of psychological resources can positively impact the daily life of users and foster human flourishing. Nowadays, mobile health represents a safe way to support health research and implement evidence-based psychological interventions. The present study aims to evaluate the effectiveness of a mobile app-based intervention program (OneUS) designed to cultivate positive emotions and positive thinking to improve overall well-being. The study is designed as a randomized controlled trial. Two hundred participants will be randomly assigned to either a mobile health intervention condition (OneUS App) or an active control condition. The intervention consists of a program to cultivate positive emotions and positive thoughts. The active control intervention will comprise a set of mental imagery exercises and daily routine recording. The primary outcome comprises optimal well-being assessed using the multidimensional PERMA-Profiler scale. The sample will include adult people from the general population, who will be assessed at 8 time points: baseline (t1), intervention (t2, t3, t4, t5, t6) post-intervention (t7) and 3-month follow-up (t8). Mobile apps seem to be promising tools to promote health and well-being. This study will evaluate the effectiveness of a mobile app (OneUS) aiming to cultivate positive emotions and positive thinking to improve well-being. The main strength of this study is the development of an evidence-based mobile health app, based on intentional mental training, to promote well-being. The limitations of this study relate to potential participant drop-out and the non-generalizability of the results to clinical populations. https://ensaiosclinicos.gov.br/rg/RBR-43hpwqk, Identifier RBR-43hpwqk.

With the rapid development of the mobile Internet, mobile reading has transcended the limitation of time and space, becoming an indispensable part of people’s living and learning. As the direct service object of mobile reading APP, users’ subjective use experience is decisive in the success or failure. It is of great significance to identify the key influencing factors of user experience of mobile reading APP. It is conducive not only to improving users reading experience and increasing users stickiness but also to improving mobile reading service quality, which is essential to promote the healthy and sustainable development of mobile reading APP. From the perspective of user experience, content analysis and questionnaire survey are used to construct the index system of influencing factors of mobile reading APP user experience, which includes 6 dimensions of reliability, usefulness, thoughtfulness, interactivity, security, and compatibility, and 21 influencing factors. Based on the decision-making trial and evaluation laboratory (DEMATEL) method, introducing the triangular fuzzy number, the fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) model is established, extending the single value of the comparison matrix to a fuzzy interval and then giving the decision makers a proper judgment space. The key influencing factors of mobile reading APP user experience are identified by algorithm design. Ultimately, the 10 key influencing factors of mobile reading APP user experience are identified, which are information quality, content richness, value fit, copyright protection, timeliness, personalized service, reading function richness, interpersonal interaction, system performance, and privacy protection, and suggestions for improving the user experience of mobile reading APP are put forward to provide reference for mobile reading APP developers. The research results not only enrich and perfect the theoretical and practical research in the mobile reading field to a certain extent, providing a new research perspective for the field of mobile reading, but also effectively solve the defects of the traditional DEMATEL method that expert judgment is subjectively biased and difficult to express with an exact number directly. The research expands the application scope of DEMATEL.