Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

Software and Mobile Apps as a Strategy for Productivity Improvement in the Construction Industry

The construction industry, known for its low productivity, is increasingly utilising software and mobile apps to enhance efficiency. However, more comprehensive research is needed to understand the effectiveness of these technology applications. The PRISMA principles utilised a scoping review methodology to ascertain pertinent studies and extract significant findings. From 2013 onwards, articles containing data on mobile applications or software designed to enhance productivity in the construction sector were obtained from multiple databases, including Emerald Insight, Science Direct, IEEE Xplore, and Google Scholar. After evaluating 2604 articles, 30 were determined to be pertinent to the study and were subsequently analysed for the review. The review identified five key themes: effectiveness, benefits, successful implementation examples, obstacles and limitations, and a comprehensive list of software and mobile apps. In addition, 71 software and mobile apps have shown potentially how these technologies can improve communication, collaboration, project management, real-time collaboration, document management, and on-the-go project information and estimating processes in the construction industry, increasing efficiency and productivity. The findings highlight the potential of these technologies such as Automation, Radio-Frequency Identification (RFID), Building Information Modeling (BIM), Augmented Reality (AR), Virtual Reality (VR), and Internet of Things (IoT) to improve efficiency and communication in the construction industry. Despite challenges such as cost, lack of awareness, resistance to change, compatibility concerns, human resources, technological and security concerns and licensing issues, the study identifies specific mobile applications and software with the potential to enhance efficiency significantly, improve productivity and streamline workflows. The broader societal impacts of construction software and mobile app development include increased efficiency, job creation, and sustainability.

Behavioral Intention to Continue Using a Library Mobile App

To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA.A research model was constructed based on the technology acceptance model.A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data.The analysis was based on structural equation modeling.The empirical results show that the perceived ease of use,the perceived usefulness,the social influence,and the facilitating conditions affected the users’behavioral intention,but their impacts were different at different times.As the usage time increases,the technology acceptance model is still universal for understanding the user perception of LMA.In addition,two extended variables(social impact and convenience)also affect the user’s behavior intention.User behavior is dynamic and changed over time.This study is important both theoretically and practically,as the results could be used to improve the service quality of LMAs and reduce the loss rate of users.Its findings may help the designers and developers of LMAs to optimize them from the perspective of a user and improve the service experience by providing a deeper understanding of the adoption behavior of information systems by LMA users.

Arabic Sentiment Analysis of Users’ Opinions of Governmental Mobile Applications

Different types of pandemics that have appeared from time to time have changed many aspects of daily life.Some governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during lockdown.The Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these applications.The manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming task.Therefore,the use of intelligent methods is necessary to analyse users’reviews and extract issues that can help in improving these apps.This research aims to support the efforts made by the Saudi government for its citizens and residents by analysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment analysis and machine learning methods.To the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi Arabia.The findings of this analysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app store.Different methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

Online and Offline Android Based Mobile Application for Mapping Health Facilities Using Google Map API. Case Study: Tanzania and Kenya Borders

The evolution of technology in 1990s resulted in the enormous growth of smartphones and the propagation of mobile applications (App) that marked new opportunities for healthcare centers and medical education. Apps have altered health services from patient’s health monitoring to specialist’s appointments and consultations from specialized health facilities. It can be argued that a healthy society can bring forth sustainable economic development to its full potential while an unhealthy society cannot. However, a free movement of people, labour and right to residence which was built across East Africa (EA) borders enabled Tanzania and Kenya borders to have enormous interactions. Subsequently, increase the risk of highly communicable diseases such as Tuberculosis and Sexually transmitted infections in such a way that medical attention is unavoidable along the borders. Statistically, Android Operating System (OS) owns 83% of Africa’s mobile OS market. In addition, 25,794,560 internet users reported by Tanzania Communications Regulatory Authority (TCRA) together with the 22.86 million internet users provided by Kenya Digital which is equivalent to 46% and 43% of internet penetration in year 2020, disclose the need for Android mobile application for mapping health facilities both online and offline using Google map API, which will solve residents’ need to healthcare services on the presence or shortage of internet connections;using either Swahili or English language via Smartphone devices. The App incorporates Monitoring and Evaluation (M & E) tool for tracking application usage which will ease Admin’s task to generate daily and monthly reports in Excel and Comma-Separated Values (CSV) formats. The developed system received positive feedback from EA citizens and residents in the Arusha region and Namanga border crossing where 90.2% of the system evaluation conducted between Dec 2020 and Apr 2021 agreed upon App usage.

Comprehensive English Assessment System Based on Mobile APPs

Comprehensive English is a professional basic course for English majors,with the most class hours and the highest credits.It can be said to be the most important course in English majors.However,the procedural assessment in the previous comprehensive English assessment system,that is,the usual assessment,was largely determined based on the subjective impression of teachers.However,with the emergence of various English learning apps,students’learning methods and content have changed a lot.With major changes,the previous assessment system has not been able to play its due role.Designing a reasonable comprehensive English assessment system based on mobile APP is the unshirkable responsibility of comprehensive English teachers.Carefully and reasonably designed comprehensive English assessment system can promote students to improve learning efficiency,reduce classroom lecture time,improve teaching effect,and play a vital role in cultivating qualified English professionals.

The Application of Mobile APP in English Learning in Senior Middle School

When students enter high school, they have a vague sense of adult psychologically, they have the desire to be independent and creative, and their confidence in their own ability is rising day by day. However, in foreign language learning, they still lack the ability of practice and self-study in foreign language learning. In particular, English teaching is limited to the traditional classroom teaching methods, it is difficult to arouse the enthusiasm of the students in higher vocational education. Using the advantages of App to apply it to English teaching can make the teaching mode interactive and fresh. At the same time, it has a convenient feedback mechanism, teachers can guide students to discuss and study outside the classroom, adjust the teaching arrangement in time, and achieve the real "student-centered".

Design and implementation of mobile APP for medication guidance related to pharmacogenomic based on APICloud platform

The mobile APP for medication guidance related to pharmacogenomic is developed to solve various practical problems, such as inconvenient reading of English database, slow updating of paper reference books and lack of shortcut for access.We extracted the medication guidance information related to the pharmacogenomic from ‘Dosing Guidelines’(http://www.pharmgkb.com), ′Table of Pharmacogenomic Biomarkers in Drug Labeling′(http://www.fda.gov/drugs/scienceresearch) and relevant authoritative books.SQLite was used to build the medication guidance information database.We designed and implemented a mobile APP for medication guidance by JavaScript programming language.The APP contained 197 drugs that have been extensively studied and have high levels of evidence.It covered 25 categories, such as anticoagulant and antiplatelet drugs, general antitumor, immunosuppressant drugs, targeted antitumor drugs, antipsychotic drugs, antiepileptic drugs, and proton pump inhibitors and so on.Users can obtain clinical significance and guidance information related to the genotype of the drug by entering the pinyin initials of the generic name of the drug.The mobile APP for medication guidance related to pharmacogenomic based on APICloud could provide practical and convenient pharmaceutical information service for clinical use.

CSLabel： An Approach for Labelling Mobile App Reviews

Mobile apps （applications） have become a popular form of software, and the app reviews by users have become an important feedback resource. Users may raise some issues in their reviews when they use apps, such as a functional bug, a network lag, or a request for a feature. Understanding these issues can help developers to focus on users＇ concerns, and help users to evaluate similar apps for download or purchase. However, we do not know which types of issues are raised in a review. Moreover, the amount of user reviews is huge and the nature of the reviews＇ text is unstructured and informal. In this paper, we analyze 3 902 user reviews from 11 mobile apps in a Chinese app store -- 360 Mobile Assistant, and uncover 17 issue types. Then, we propose an approach CSLabel that can label user reviews based on the raised issue types. CSLabel uses a cost-sensitive learning method to mitigate the effects of the imbalanced data, and optimizes the setting of the support vector machine （SVM） classifier＇s kernel function. Results show that CSLabel can correctly label reviews with the precision of 66.5%, the recall of 69.8%, and the F1 measure of 69.8%. In comparison with the state-of-the-art approach, CSLabel improves the precision by 14%, the recall by 30%, the F1 measure by 22%. Finally, we apply our approach to two real scenarios： 1） we provide an overview of 1 076 786 user reviews from 1 100 apps in the 360 Mobile Assistant and 2） we find that some issue types have a negative correlation with users＇ evaluation of apps.

Mediating role of brand app trust in the relationship between antecedents and purchase intentions-Iranian B2C mobile apps

This study investigates the mediating role of brand app trust in the relationship between brand app antecedents and purchase intentions via a brand mobile app.It explores the mediating potential of brand and platform trust in this relationship between antecedents and purchase intentions and also highlights which brand antecedents are useful for directly or indirectly establishing trust towards purchasing via a mobile app in the Iranian mobile commerce market.This study uses survey data collected through an online questionnaire form and applies the partial least squares method to extract its findings.All of the estimation results are found to be unbiased and robust.The results show that brand app trust plays a mediating role in the relationship between the brand app antecedents of word-of-mouth recommendation,subjective norms,perceived image(social antecedents),mobile computing self-efficacy(consumer-based antecedent),and perceived ease of use(system antecedent)and purchase intentions via a brand mobile app in Iran.

What leads to readers' satisfaction with the mobile news apps service? An investigation into the roles of content originality and user experience

Purpose: This study aims to explore whether content originality and user experience have positive effects on online news readers’ satisfaction with the mobile apps service.Design/methodology/approach: Data was collected via a Web-based survey. Data analysis of this study can be divided into two stages. In the first stage, a descriptive statistical analysis was conducted based on a sample of 612 respondents. In the second stage, the correlation among content originality, user experience and satisfaction was analyzed based on a sample of 377 mobile news apps users. Findings: Results of the first stage showed that social media and mobile news apps were the most important tools for users to access news, and different types of media were playing complementary roles in information transmission. Users held a positive attitude toward their mobile news reading experience and they described news they read on mobile apps with such words as "interesting", "instant", "positive", "profound", and "ironic". Results of the second stage confirmed our hypothesis that content originality and user experience both had positive impacts on user satisfaction.Research limitations: The questionnaires were distributed entirely online, so the sample may not be representative of the general population being studied and thus undermine the reliability and generalization of the findings to some extent. Moreover, this study adopted only one method(survey) and more methods such as interviews can be used to improve the accuracy of the results.Practical implications: The findings of this study can not only provide insights into a better understanding of users’ mobile reading behavior, but also help mobile information service providers attract more users.Originality/value: This is one of the first studies to explore the effects of content originality and user experience on online news readers’ satisfaction with the mobile apps service.

The Land- Potential Knowledge System (LandPKS): mobile apps and collaboration for optimizing climate change investments

Massive investments in climate change mitigation and adaptation are projected during coming decades.Many of these investments will seek to modify how land is managed.The return on both types of investments can be increased through an understanding of land potential:the potential of the land to support primary production and ecosystem services,and its resilience.A Land-Potential Knowledge System(LandPKS)is being developed and implemented to provide individual users with point-based estimates of land potential based on the integration of simple,geo-tagged user inputs with cloud-based information and knowledge.This system will rely on mobile phones for knowledge and information exchange,and use cloud computing to integrate,interpret,and access relevant knowledge and information,including local knowledge about land with similar potential.The system will initially provide management options based on long-term land potential,which depends on climate,to-pography,and relatively static soil properties,such as soil texture,depth,and mineralogy.Future mod-ules will provide more specific management information based on the status of relatively dynamic soil properties such as organic matter and nutrient content,and of weather.The paper includes a discus-sion of how this system can be used to help distinguish between meteorological and edaphic drought.

Lessons on mobile apps for COVID-19 from China

The COVID-19 pandemic has impacted the global society and human life profoundly.Many countries have launched COVID-19 mobile apps with a wide range in how these apps work.While it is hoped that these apps can assist in the fight against COVID-19,many are worried about user privacy.China implemented“health code”systems,which assigned neighborhoods and citizens a specific health code,meant to indicate their risk of having been exposed to COVID-19.The most widely used health code systems were hosted on the popular apps WeChat and Alipay,each with billions of users.Some experts argued that China’s use of mobile applications was essential to its successful combat against COVID-19.Included in this study are a summary of mobile technology usage in China,a review of previous studies of mobile technology in healthcare,and a brief survey of some existing mobile applications for COVID-19 that were imple-mented.Also included are outcomes of interviews with healthcare and public safety experts and a public survey to understand how mobile applications were used in China’s response to COVID-19.The interviews revealed four important themes:personal privacy,community involvement,government involvement,and situational speci-ficity.It was found that a key concern was maintaining a balance between collecting and utilizing personal information,as well as protecting this information.In addition,close collaboration between local communities and the national government was essential.Mobile applications assisted in communication and coordination but did not replace the work of people such as delivery drivers and contact tracers.Our results also showed that there was room for improvement,especially accessibility for the elderly or those unfamiliar with technology.Similar results were obtained from our survey.It was interesting to find that the apps were mostly used for“accessing information on COVID-19.”In addition,respondents overwhelmingly identified“information”as the most valuable feature of COVID-19 apps.Both interview and survey results revealed the importance of providing information as a primary function of COVID-19 apps.Based on our findings we distilled four main lessons:mobile applications should assist in existing COVID-19 responses,inform users,protect users’personal information,and adapt to users’environments.We recommend that public health officials and app developers take these lessons into consideration when de-veloping COVID-19 related mobile applications.In addition,we encourage researchers to utilize this report as a jumping offpoint for further research.

Research on Blended Teaching Model in College English Based on Mobile Learning App

Mobile learning is the general trend of the times and the inevitable choice for the reform and development of college English teaching.This article attempts to use blended learning theory,mobile learning theory,and instructional design theory as a guide.In many English mobile learning apps,Superstar Learning Link is used as an example to design an online and offline blended teaching mode.It proposes thinking expansion and interaction in pre-class stage.Consolidation of input and outputoriented process are during class and evaluation and sublimation are made after class.The essay is aimed to break the boundaries between traditional teaching and mobile learning,combining synchronous learning with personalized learning in order to improve comprehensive levels of English.

How mobile messaging apps users share information on WeChat: The role of demographic variables

Purpose： We conducted an empirical study to find out the role of demographic variables in affecting information sharing behaviors of college student users of WeChat.Design/methodology/approach： A questionnaire survey was carried out to investigate the relationship between demographic variables （gender, grade level, dating status, and singleparent family background） and information sharing behaviors of WeChat users. The participants were college students and a total of 255 valid questionnaires were collected. Data was analyzed using descriptive statistics and multiple regression analysis.Findings： Grade level and single-parent family background were found to be significantly correlated with information sharing behaviors whereas no effect of gender was found on information sharing behaviors. Dating status had no significant impact on user browsing behavior, but was related to users＇ publishing posts and posting replies.Implications： The study will help understand individual differences in information sharing among WeChat users.Limitations： First, the relatively small sample size is a limitation in exploring the effects of demographic variables on user information sharing behaviors. Second, this study only used questionnaire surveys to collect data and more research methods such as interviews should be adopted to improve the accuracy of the study results.Originality/value： This paper is one of the first studies to explore the relationship between demographic variables and user information sharing behaviors on WeChat.

The Application of Mobile Phone APP in the Follow-up Management of Hospital

Objective:Explore the application of mobile phone APP in the follow-up management of hospital in the information age,to build a harmonious doctor-patient relationship,improve the effective follow-up rate and promote the rehabilitation of patients.Methods:Compare and analyze the traditional telephone follow-up mode and the mode of mobile phone APP with telephone follow-ups.Results:In 2016,with telephone follow-ups only,the effective rate was 91.3%,the patient satisfaction rate was 92.6%.In 2017,besides telephone follow-ups,we used mobile phone APP,the effective follow-up rate got up to 96.2%,the satisfaction rate of patients got up to 98.1%.Conclusion:Compared with the traditional follow-up model,mobile phone APP follow-up model can improve the clinical follow-up service and the compliance of patients,help to reduce failures of follow-up.With mobile phone APP,it’s much more convenient and effective for doctors to communicate with patients,and it is better for the rehabilitation of patients with disease.

Persuasive Technology for the Future of Smoking Cessation*

This paper explores the integration of persuasive technology into smoking cessation efforts through the development and evaluation of a mobile app, “No-Smoke.” Leveraging compelling features like social support, tracking, planning, and motivation, the app aims to augment user engagement and support the process of quitting smoking. The efficacy of these features has been substantiated through both automated testing and user feedback, highlighting their potential to enhance awareness, motivation, and behavior modification. Despite notable successes, limitations, including a limited user base and uncertainties regarding long-term efficacy, have been acknowledged, stemming from the inherent complexities of smoking cessation. Nevertheless, based on user experiences and feedback, “No-Smoke” represents a promising advancement in the use of technology for public health interventions, particularly in the realm of smoking cessation. To address existing challenges, future research is recommended to encompass a comprehensive, long-term study involving a larger and more diverse user base. Additionally, further investigation should focus on personalization enhancements and the integration of machine learning algorithms to better understand and respond to user behavior.

Analysis of Key Attributes Influencing the User Satisfaction towards Applications

This research aims to find out the key attributes influencing the user trust towards applications on the mobile application store. In this research, both the experimental data set and the evaluation results of analysis are described. The analysis results include the test results of analysis of variance （ANOVA） and correlation analysis. In ANOVA, the attributes affecting user rating are derived and applied to the correlation analysis to evaluate the degree of correlation towards user rating, and in the last stage the positive or negative relationship with user satisfaction is figured out.

Potential of plant identification apps in urban forestry studies in China:comparison of recognition accuracy and user experience of five apps

Information on species composition of an urban forest is essential for its management.However,to obtain this information becomes increasingly difficult due to limited taxonomic expertise.In this study,we tested the possibility of using plant identification applications running on mobile platforms to fill this vacuum.Five plant identification apps were compared for their potential in identifying urban tree species in China.An online survey was conducted to determine the features of apps that contributed to users’satisfaction.The results show that identification accuracy varied significantly among the apps.The best performer achieved an accuracy of 74.6%at the species level,which is comparable to the accuracy by professionals in field surveys.Among the features of apps,accuracy of identification was the most important factor that contributed to users’satisfaction.However,plant identification apps did not perform well when used on rare species or outside of the regions where they have been developed.Results indicate that plant identification apps have great potential in urban forest studies and management,but users need to be cautious when deciding which one to use.

The application of APP （application programs） in college English listening teaching

Chinese college students have some drawbacks in English learning and mastering. Through a dozen years of English learning, some of them have high ability of passing examinations, but the practical application ability is barely satisfactory with relatively poor listening level and oral expression ability. The objective cause for this situation is the relatively single and stylization English teaching model used by traditional colleges and universities. This model only emphasizes learning on class which greatly harms students＇ English learning enthusiasm and initiatives. The result is that although the students passed CET4 and CET6 long time before their graduation, they still not dare to open their mouth to speaking concerning face to face English communications. Over the years, the researches on how to improve college students＇ English application ability never stop and they did obtain some achievements and show some opportunities, for example, if we can bring APP （application programs） into college English listening class, it will largely meet students requirements on English learning and this can also replenish and perfect traditional English teaching model.