相关论文: A comparative study of Bot Detection techniques me…

Studying temporal dynamics of topics in social media is very useful to understand online user behaviors. Most of the existing work on this subject usually monitors the global trends, ignoring variation among communities. Since users from…

Current research on users` perspectives of cyber security and privacy related to traditional and smart devices at home is very active, but the focus is often more on specific modern devices such as mobile and smart IoT devices in a home…

Misbehavior in online social networks (OSN) is an ever-growing phenomenon. The research to date tends to focus on the deployment of machine learning to identify and classify types of misbehavior such as bullying, aggression, and racism to…

COVID-19 pandemic has generated what public health officials called an infodemic of misinformation. As social distancing and stay-at-home orders came into effect, many turned to social media for socializing. This increase in social media…

Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis. We define this task as being able to classify a tweet as racist,…

Understanding the characteristics of public attention and sentiment is an essential prerequisite for appropriate crisis management during adverse health events. This is even more crucial during a pandemic such as COVID-19, as primary…

Online social media are key platforms for the public to discuss political issues. As a result, researchers have used data from these platforms to analyze public opinions and forecast election results. Recent studies reveal the existence of…

The outbreak of covid-19 started many months ago, the reported origin was in Wuhan Market, China. Fastly, this virus was propagated to other countries because the access to international travels is affordable and many countries have a…

Online social media provides a channel for monitoring people's social behaviors and their mental distress. Due to the restrictions imposed by COVID-19 people are increasingly using online social networks to express their feelings.…

During sudden onset crisis events, the presence of spam, rumors and fake content on Twitter reduces the value of information contained on its messages (or "tweets"). A possible solution to this problem is to use machine learning to…

Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. In this paper we adapt existing bio-surveillance algorithms to…

COVID-19 has brought about many changes in social dynamics. Stay-at-home orders and disruptions in school teaching can influence bullying behavior in-person and online, both of which leading to negative outcomes in victims. To study…

The study aims to understand Twitter users' discourse and psychological reactions to COVID-19. We use machine learning techniques to analyze about 1.9 million Tweets (written in English) related to coronavirus collected from January 23 to…

The COVID-19 pandemic has produced a flurry of online activity on social media sites. As such, analysis of social media data during the COVID-19 pandemic can produce unique insights into discussion topics and how those topics evolve over…

This paper illustrates five different techniques to assess the distinctiveness of topics, key terms and features, speed of information dissemination, and network behaviors for Covid19 tweets. First, we use pattern matching and second, topic…

Social media platforms facilitate mankind a data-driven world by enabling billions of people to share their thoughts and activities ubiquitously. This huge collection of data, if analysed properly, can provide useful insights into people's…

As of 2020 when the COVID-19 pandemic is full-blown on a global scale, people's need to have access to legitimate information regarding COVID-19 is more urgent than ever, especially via online media where the abundance of irrelevant…

False information spreads on social media, and fact-checking is a potential countermeasure. However, there is a severe shortage of fact-checkers; an efficient way to scale fact-checking is desperately needed, especially in pandemics like…

Signature-based botnet detection methods identify botnets by recognizing Command and Control (C\&C) traffic and can be ineffective for botnets that use new and sophisticate mechanisms for such communications. To address these limitations,…

The outbreak of the COVID-19 leads to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking…