Related papers: Coordinated Reply Attacks in Influence Operations:…

Coordinated campaigns on social media play a critical role in shaping crisis information environments, particularly during the onset of conflicts when uncertainty is high and verified information is scarce. We study the interplay between…

This paper presents four examples of different ways that coordinated influence operations exert pressure on the prominence of ideas on social networks. We argue that these examples illustrate the four archetypical paths to influence:…

Alas, coordinated hate attacks, or raids, are becoming increasingly common online. In a nutshell, these are perpetrated by a group of aggressors who organize and coordinate operations on a platform (e.g., 4chan) to target victims on another…

Coordinated disinformation campaigns are used to influence social media users, potentially leading to offline violence. In this study, we introduce a general methodology to uncover coordinated messaging through analysis of user parleys on…

Many works related to Twitter aim at characterizing its users in some way: role on the service (spammers, bots, organizations, etc.), nature of the user (socio-professional category, age, etc.), topics of interest , and others. However, for…

In modeling social interaction online, it is important to understand when people are reacting to each other. Many systems have explicit indicators of replies, such as threading in discussion forums or replies and retweets in Twitter.…

The daily exposure of social media users to propaganda and disinformation campaigns has reinvigorated the need to investigate the local and global patterns of diffusion of different (mis)information content on social media. Echo chambers…

Large-scale online campaigns, malicious or otherwise, require a significant degree of coordination among participants, which sparked interest in the study of coordinated online behavior. State-of-the-art methods for detecting coordinated…

Twitter is used for a variety of reasons, including information dissemination, marketing, political organizing and to spread propaganda, spamming, promotion, conversations, and so on. Characterizing these activities and categorizing…

This study investigates adversarial attacks conducted to distort voter model dynamics in complex networks. Specifically, a simple adversarial attack method is proposed to hold the state of opinions of an individual closer to the target…

This study investigates behavior-targeted attacks on reinforcement learning and their countermeasures. Behavior-targeted attacks aim to manipulate the victim's behavior as desired by the adversary through adversarial interventions in state…

Cyberaggression has been studied in various contexts and online social platforms, and modeled on different data using state-of-the-art machine and deep learning algorithms to enable automatic detection and blocking of this behavior. Users…

Measuring the impact and success of human performance is common in various disciplines, including art, science, and sports. Quantifying impact also plays a key role on social media, where impact is usually defined as the reach of a user's…

This paper considers the problem of automatically characterizing overall attitudes and biases that may be associated with emerging information operations via artificial intelligence. Accurate analysis of these emerging topics usually…

The ability to detect coordinated activity in communication networks is an ongoing challenge. Prior approaches emphasize considering any activity exceeding a specific threshold of similarity to be coordinated. However, identifying such a…

Social media platforms, particularly Twitter, have become pivotal arenas for influence campaigns, often orchestrated by state-sponsored information operations (IOs). This paper delves into the detection of key players driving IOs by…

Centrality is one of the most studied concepts in social network analysis. There is a huge literature regarding centrality measures, as ways to identify the most relevant users in a social network. The challenge is to find measures that can…

Digital traces of conversations in micro-blogging platforms and OSNs provide information about user opinion with a high degree of resolution. These information sources can be exploited to under- stand and monitor collective behaviors. In…

Social media is often viewed as a sensor into various societal events such as disease outbreaks, protests, and elections. We describe the use of social media as a crowdsourced sensor to gain insight into ongoing cyber-attacks. Our approach…

More and more investors and machine learning models rely on social media (e.g., Twitter and Reddit) to gather real-time information and sentiment to predict stock price movements. Although text-based models are known to be vulnerable to…