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Users online tend to acquire information adhering to their system of beliefs and to ignore dissenting information. Such dynamics might affect page popularity. In this paper we introduce an algorithm, that we call PopRank, to assess both the…
Social media platforms enable the rapid dissemination and consumption of information. However, users instantly consume such content regardless of the reliability of the shared data. Consequently, the latter crowdsourcing model is exposed to…
In an era where misinformation spreads freely, fact-checking (FC) plays a crucial role in verifying claims and promoting reliable information. While automated fact-checking (AFC) has advanced significantly, existing systems remain…
Fake news, misinformation, and unverifiable facts on social media platforms propagate disharmony and affect society, especially when dealing with an epidemic like COVID-19. The task of Fake News Detection aims to tackle the effects of such…
Online political advertising has grown significantly over the last few years. To monitor online sponsored political discourse, companies such as Facebook, Google, and Twitter have created public Ad Libraries collecting the political ads…
Young people are increasingly exposed to adverse effects of data-driven profiling, recommending, and manipulation on social media platforms, most of them without adequate understanding of the mechanisms that drive these platforms. In the…
Currently, many users of Social Network Sites are insufficiently aware of who can see their shared personal items. Nonetheless, most approaches focus on enhancing privacy in Social Networks through improved privacy settings, neglecting the…
Facially manipulated images and videos or DeepFakes can be used maliciously to fuel misinformation or defame individuals. Therefore, detecting DeepFakes is crucial to increase the credibility of social media platforms and other media…
Although mobile ad frauds have been widespread, state-of-the-art approaches in the literature have mainly focused on detecting the so-called static placement frauds, where only a single UI state is involved and can be identified based on…
Recent years have seen a sharp rise in adblocker use, driven by increased web tracking and personalized ads. However, a significant issue for adblocker users is the web breakages they encounter, which worsens their browsing experience and…
Web traffic is a valuable data source, typically used in the marketing space to track brand awareness and advertising effectiveness. However, web traffic is also a rich source of information for cybersecurity monitoring efforts. To better…
Online users generate tremendous amounts of data. To better serve users, it is required to share the user-related data among researchers, advertisers and application developers. Publishing such data would raise more concerns on user…
This paper investigates the usage patterns of Facebook among different demographics in the United States, focusing on the consumption of political information and its variability across age, gender, and ethnicity. Employing a novel data…
We quantify Facebook's ability to build shadow profiles by tracking individuals across the web, irrespective of whether they are users of the social network. For a representative sample of US Internet users, we find that Facebook is able to…
In recent years, the reliability of information on the Internet has emerged as a crucial issue of modern society. Social network sites (SNSs) have revolutionized the way in which information is spread by allowing users to freely share…
Intelligent systems for the annotation of media content are increasingly being used for the automation of parts of social science research. In this domain the problem of integrating various Artificial Intelligence (AI) algorithms into a…
Autonomous driving is among the largest domains in which deep learning has been fundamental for progress within the last years. The rise of datasets went hand in hand with this development. All the more striking is the fact that researchers…
We present an approach for selecting objectively informative and subjectively helpful annotations to social media posts. We draw on data from on an online environment where contributors annotate misinformation and simultaneously rate the…
Efforts by online ad publishers to circumvent traditional ad blockers towards regaining fiduciary benefits, have been demonstrably successful. As a result, there have recently emerged a set of adblockers that apply machine learning instead…
In the past decade, the social networks platforms and micro-blogging sites such as Facebook, Twitter, Instagram, and Weibo have become an integral part of our day-to-day activities and is widely used all over the world by billions of users…