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 mo...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.展开更多
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 th...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.展开更多
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 a...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.展开更多
The building information model/modeling （BIM） technology is currently applied in a broad range of applications and research for facility management, while the BIM-based mobile FM is difficult owing to various factor...The building information model/modeling （BIM） technology is currently applied in a broad range of applications and research for facility management, while the BIM-based mobile FM is difficult owing to various factors and environments. For example, the mobile applications usually require frequent cross-equipment compatibility. This paper proposes a reasonable BIM-based FM cross-platform framework and develops a mobile application on the basis of an existing BIM-based FM system. The developed mobile application is applied in a case study of a metro station project in Guangzhou to verify its effectiveness in FM practice. It helps maintenance staff in viewing BIMs, accessing related information, and updating maintenance records in a unique platform. The test results demonstrate that the proposed BIM-based cross-platform framework meet the FM application requirements and supports the extension of FM functions.展开更多
Recently,various mobile apps have included more features to improve user convenience.Mobile operating systems load as many apps into memory for faster app launching and execution.The least recently used(LRU)-based ter...Recently,various mobile apps have included more features to improve user convenience.Mobile operating systems load as many apps into memory for faster app launching and execution.The least recently used(LRU)-based termination of cached apps is a widely adopted approach when free space of the main memory is running low.However,the LRUbased cached app termination does not distinguish between frequently or infrequently used apps.The app launch performance degrades if LRU terminates frequently used apps.Recent studies have suggested the potential of using users’app usage patterns to predict the next app launch and address the limitations of the current least recently used(LRU)approach.However,existing methods only focus on predicting the probability of the next launch and do not consider how soon the app will launch again.In this paper,we present a new approach for predicting future app launches by utilizing the relaunch distance.We define the relaunch distance as the interval between two consecutive launches of an app and propose a memory management based on app relaunch prediction(M2ARP).M2ARP utilizes past app usage patterns to predict the relaunch distance.It uses the predicted relaunch distance to determine which apps are least likely to be launched soon and terminate them to improve the efficiency of the main memory.展开更多
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 in...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.展开更多
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 collec...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.展开更多
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 surve...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.展开更多
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 forei...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".展开更多
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 hav...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.展开更多
This research is interested in the user ratings of Apps on Apple Stores. The purpose of this research is to have a better understanding of some characteristics of the good Apps on Apple Store so Apps makers can potent...This research is interested in the user ratings of Apps on Apple Stores. The purpose of this research is to have a better understanding of some characteristics of the good Apps on Apple Store so Apps makers can potentially focus on these traits to maximize their profit. The data for this research is collected from kaggle.com, and originally collected from iTunes Search API, according to the abstract of the data. Four different attributes contribute directly toward an App’s user rating: rating_count_tot, rating_count_ver, user_rating and user_rating_ver. The relationship between Apps receiving higher ratings and Apps receiving lower ratings is analyzed using Exploratory Data Analysis and Data Science technique “clustering” on their numerical attributes. Apps, which are represented as a data point, with similar characteristics in rating are classified as belonging to the same cluster, while common characteristics of all Apps in the same clusters are the determining traits of Apps for that cluster. Both techniques are achieved using Google Colab and libraries including pandas, numpy, seaborn, and matplotlib. The data reveals direct correlation from number of devices supported and languages supported to user rating and inverse correlation from size and price of the App to user rating. In conclusion, free small Apps that many different types of users are able to use are generally well rated by most users, according to the data.展开更多
文摘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.
文摘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.
文摘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.
基金Supported by the National High-tech Research and Development Program of China(2013AA041307)the National Natural Science Foundation of China(51478249)the Tsinghua University-Glodon Joint Research Centre for Building Information Model
文摘The building information model/modeling （BIM） technology is currently applied in a broad range of applications and research for facility management, while the BIM-based mobile FM is difficult owing to various factors and environments. For example, the mobile applications usually require frequent cross-equipment compatibility. This paper proposes a reasonable BIM-based FM cross-platform framework and develops a mobile application on the basis of an existing BIM-based FM system. The developed mobile application is applied in a case study of a metro station project in Guangzhou to verify its effectiveness in FM practice. It helps maintenance staff in viewing BIMs, accessing related information, and updating maintenance records in a unique platform. The test results demonstrate that the proposed BIM-based cross-platform framework meet the FM application requirements and supports the extension of FM functions.
基金This work was supported in part by the National Research Foundation of Korea(NRF)Grant funded by the Korea Government(MSIT)under Grant 2020R1A2C100526513in part by the R&D Program for Forest Science Technology(Project No.2021338C10-2323-CD02)provided by Korea Forest Service(Korea Forestry Promotion Institute).
文摘Recently,various mobile apps have included more features to improve user convenience.Mobile operating systems load as many apps into memory for faster app launching and execution.The least recently used(LRU)-based termination of cached apps is a widely adopted approach when free space of the main memory is running low.However,the LRUbased cached app termination does not distinguish between frequently or infrequently used apps.The app launch performance degrades if LRU terminates frequently used apps.Recent studies have suggested the potential of using users’app usage patterns to predict the next app launch and address the limitations of the current least recently used(LRU)approach.However,existing methods only focus on predicting the probability of the next launch and do not consider how soon the app will launch again.In this paper,we present a new approach for predicting future app launches by utilizing the relaunch distance.We define the relaunch distance as the interval between two consecutive launches of an app and propose a memory management based on app relaunch prediction(M2ARP).M2ARP utilizes past app usage patterns to predict the relaunch distance.It uses the predicted relaunch distance to determine which apps are least likely to be launched soon and terminate them to improve the efficiency of the main memory.
基金“Design and Practice of Blended Teaching Model in College English Based on Mobile Learning App”,the“Thirteenth Five-Year Plan”project on Education and Science of Heilongjiang Province in 2018(Project Number:GJC1318030)。
文摘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.
文摘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.
基金jointly supported by the National Social Science Foundation of China(Grant No.:14BTQ044)Wuhan University Academic Development Plan for Scholars born after the 1970s for the project of"research on Internet user behavior"Wuhan University Postgraduate English Course on Internet User Behavior and Luo Jia Youth Scholar of Wuhan University
文摘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.
文摘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".
文摘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.
文摘This research is interested in the user ratings of Apps on Apple Stores. The purpose of this research is to have a better understanding of some characteristics of the good Apps on Apple Store so Apps makers can potentially focus on these traits to maximize their profit. The data for this research is collected from kaggle.com, and originally collected from iTunes Search API, according to the abstract of the data. Four different attributes contribute directly toward an App’s user rating: rating_count_tot, rating_count_ver, user_rating and user_rating_ver. The relationship between Apps receiving higher ratings and Apps receiving lower ratings is analyzed using Exploratory Data Analysis and Data Science technique “clustering” on their numerical attributes. Apps, which are represented as a data point, with similar characteristics in rating are classified as belonging to the same cluster, while common characteristics of all Apps in the same clusters are the determining traits of Apps for that cluster. Both techniques are achieved using Google Colab and libraries including pandas, numpy, seaborn, and matplotlib. The data reveals direct correlation from number of devices supported and languages supported to user rating and inverse correlation from size and price of the App to user rating. In conclusion, free small Apps that many different types of users are able to use are generally well rated by most users, according to the data.
