Twitter data have been used widely in times of pandemics and crises. Currently, the world is suffering from the outbreak of new coronavirus disease 2019 , in which the COVID-19 virus has infected more than one hundred and twenty million people worldwide with more than two million deaths. Consequently, people tend to share COVID-19-related content on social media extensively. As a new pandemic, only a small number of studies have been conducted to analyze COVID-19-related tweets, and even fewer were meant for Arabic tweets. This research explores the influence of the COVID-19 pandemic on Saudi users' tweeting behavior. In particular, the research adopts a social network analysis (SNA) for COVID-19 Arabic tweets. This approach is interesting, as it is based on analysis of social structures, such as Twitter users and the relationships among them, through the use of networks and graph theory without the contents of the tweets themselves. Based on 8905 collected Arabic tweets, this research resulted in three main contributions: 1) a visualization of the social network for COVID-19 tweets of Saudi users, 2) an identification of information sources that Twitter users employ during the COVID-19 pandemic, and 3) an identification of the most popular influencers among users of COVID-19 tweets. The results of this study may help identify the most popular Twitter influencers and those who deliver the information to Twitter users, utilizing them to increase awareness and deliver information and instructions to overcome the COVID-19 pandemic.
Considering that application security is an important aspect, especially nowadays with the increase in technology and the number of fraudsters. It should be noted that determining the security of an application is a difficult task, especially since most fraudsters have become skilled and professional at manipulating people and stealing their sensitive data. Therefore, we pay attention to trying to spot insecurity apps, by analyzing user feedback on the Google Play platform and using sentiment analysis to determine the apps level of security. As it is known, user reviews reflect their experiments and experiences in addition to their feelings and satisfaction with the application or not. But unfortunately, not all of these reviews are real, and as is known, the fake reviews do not reflect the sincerity of feelings, so we have been keen in our work to filter the reviews to be the result is accurate and correct. This study is useful for both users wanting to install android apps and for developers interested in app optimization.
Incident management in College of Computer needs to be processed and stored in order to give fast services in terms of solving staff and student's problems and to make the Technical Support Department agent's job easier. Therefore, knowledge base is needed as an incident storage media for the Technical Support Department. This paper propose an Incident Management system using Knowledge base called "COC_HelpDesk". The validation of the system is shown through an experiment study carried out by the Technical Support Department agents.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.