Related papers: A machine-learning approach to Detect users' suspi…

Many researchers have been concerned with whether social media has a negative impact on the well-being of their audience. With the popularity of social networking sites (SNS) steadily increasing, psychological and social sciences have shown…

Investigating efficiently the data collected from a system's activity can help to detect malicious attempts and better understand the context behind past incident occurrences. Nowadays, several solutions can be used to monitor system…

The presence of Super-Apps have changed the way we think about the interactions between users and commerce. It then comes as no surprise that it is also redefining the way banking is done. The paper investigates how different interactions…

Hate speech, offensive language, aggression, racism, sexism, and other abusive language are common phenomena in social media. There is a need for Artificial Intelligence(AI)based intervention which can filter hate content at scale. Most…

To what extent user's stance towards a given topic could be inferred? Most of the studies on stance detection have focused on analysing user's posts on a given topic to predict the stance. However, the stance in social media can be inferred…

This paper introduces the concept of Open Source Intelligence (OSINT) as an important application in intelligent profiling of individuals. With a variety of tools available, significant data shall be obtained on an individual as a…

Due to the proliferation of online social networks (OSNs), users find themselves participating in multiple OSNs. These users leave their activity traces as they maintain friendships and interact with other users in these OSNs. In this work,…

Textual emotional intelligence is playing a ubiquitously important role in leveraging human emotions on social media platforms. Social media platforms are privileged with emotional content and are leveraged for various purposes like opinion…

Online social network analysis has attracted great attention with a vast number of users sharing information and availability of APIs that help to crawl online social network data. In this paper, we study the research studies that are…

One major problem with cyberbullying research is the lack of data, since researchers are traditionally forced to rely on survey data where victims and perpetrators self-report their impressions. In this paper, an automatic data collection…

Online social networks are often subject to influence campaigns by malicious actors through the use of automated accounts known as bots. We consider the problem of detecting bots in online social networks and assessing their impact on the…

Social media platforms have become vital spaces for public discourse, serving as modern agor\`as where a wide range of voices influence societal narratives. However, their open nature also makes them vulnerable to exploitation by malicious…

To remain aware of the fast-evolving cyber threat landscape, open-source Cyber Threat Intelligence (OSCTI) has received growing attention from the community. Commonly, knowledge about threats is presented in a vast number of OSCTI reports.…

Community detection in social networks is widely studied because of its importance in uncovering how people connect and interact. However, little attention has been given to community structure in Facebook public pages. In this study, we…

The primary objective of an anonymity tool is to protect the anonymity of its users through the implementation of strong encryption and obfuscation techniques. As a result, it becomes very difficult to monitor and identify users activities…

Cyber-security analysts face an increasingly large number of alerts received on any given day. This is mainly due to the low precision of many existing methods to detect threats, producing a substantial number of false positives. Usually,…

Social media platforms have transformed traditional communication methods by allowing users worldwide to communicate instantly, openly, and frequently. People use social media to express their opinion and share their personal stories and…

Mental health disorders are a global crisis. While various datasets exist for detecting such disorders, there remains a critical gap in identifying individuals actively seeking help. This paper introduces a novel dataset, M-Help,…

Social media accounts engaging in online manipulation can change their behaviors for re-purposing or to evade detection. Existing detection systems are built on features that do not exploit such behavioral patterns. Here we investigate the…

Suicidal ideation detection from social media is an evolving research with great challenges. Many of the people who have the tendency to suicide share their thoughts and opinions through social media platforms. As part of many researches it…