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The presence and complexity of political Twitter bots has increased in recent years, making it a very difficult task to recognize these accounts from real, human users. We intended to provide an answer to the following question: are…
Bots are social media accounts that automate interaction with other users, and they are active on the StrongerIn-Brexit conversation happening over Twitter. These automated scripts generate content through these platforms and then interact…
Online Social Media represent a pervasive source of information able to reach a huge audience. Sadly, recent studies show how online social bots (automated, often malicious accounts, populating social networks and mimicking genuine users)…
This paper introduces LABurst, a general technique for identifying key moments, or moments of high impact, in social media streams without the need for domain-specific information or seed keywords. We leverage machine learning to model…
Web 2.0 applications like Twitter or Facebook create a continuous stream of information. This demands new ways of analysis in order to offer insight into this stream right at the moment of the creation of the information, because lots of…
There has been much effort on studying how social media sites, such as Twitter, help propagate information in different situations, including spreading alerts and SOS messages in an emergency. However, existing work has not addressed how to…
An infodemic is an emerging phenomenon caused by an overabundance of information online. This proliferation of information makes it difficult for the public to distinguish trustworthy news and credible information from untrustworthy sites…
Streams of user-generated content in social media exhibit patterns of collective attention across diverse topics, with temporal structures determined both by exogenous factors and endogenous factors. Teasing apart different topics and…
Twitter is recognized as a crucial platform for the dissemination and gathering of Cyber Threat Intelligence (CTI). Its capability to provide real-time, actionable intelligence makes it an indispensable tool for detecting security events,…
We explore the effects of coordinated users (i.e., users characterized by an unexpected, suspicious, or exceptional similarity) in information spreading on Twitter by quantifying the efficacy of their tactics in deceiving feed algorithms to…
The impact of online social media on societal events and institutions is profound; and with the rapid increases in user uptake, we are just starting to understand its ramifications. Social scientists and practitioners who model online…
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…
Nowadays, many platforms on the Web offer organized events, allowing users to be organizers or participants. For such platforms, it is beneficial to predict potential event participants. Existing work on this problem tends to borrow…
On social platforms like Twitter, strategic targeted attacks are becoming increasingly common, especially against vulnerable groups such as female journalists. Two key challenges in identifying strategic online behavior are the complex…
Twitter is one of the most popular microblogging services in the world. The great amount of information within Twitter makes it an important information channel for people to learn and share news. Twitter hashtag is an popular feature that…
Social media platforms such as Twitter (now known as X) have revolutionized how the public engage with important societal and political topics. Recently, climate change discussions on social media became a catalyst for political…
In social network Twitter, users can interact with each other and spread information via retweets. These millions of interactions may result in media events whose influence goes beyond Twitter framework. In this paper, we thoroughly explore…
This paper describes the analysis of quantitative characteristics of frequent sets and association rules in the posts of Twitter microblogs related to different event discussions. For the analysis, we used a theory of frequent sets,…
We report the first, to the best of our knowledge, hand-in-hand collaboration between human rights activists and machine learners, leveraging crowd-sourcing to study online abuse against women on Twitter. On a technical front, we carefully…
Social media streams contain large and diverse amount of information, ranging from daily-life stories to the latest global and local events and news. Twitter, especially, allows a fast spread of events happening real time, and enables…