As popular tools for spreading spam andmalware, Sybils (or fake accounts) pose a serious threat to online communities such as Online Social Networks (OSNs). Today, sophisticated attackers are creating realistic Sybils that effectively befriend legitimate users, rendering most automated Sybil detection techniques ineffective. In this paper, we explore the feasibility of a crowdsourced Sybil dete...

We characterise mutations between fake weighted projective spaces, and give explicit formulas for how the weights and multiplicity change under mutation. In particular, we prove that multiplicity-preserving mutations between fake weighted projective spaces are mutations over edges of the corresponding simplices. As an application, we analyse the canonical and terminal fake weighted projective s...

Numerous fake images spread on social media today and can severely jeopardize the credibility of online content to public. In this paper, we employ deep networks to learn distinct fake image related features. In contrast to authentic images, fake images tend to be eye-catching and visually striking. Compared with traditional visual recognition tasks, it is extremely challenging to understand th...

The current study focused on the production of fake geminates across different boundary types in English to investigate the hypothesis that word-internal fake geminates may differ from those that arise across a word boundary. In this study, word-internal geminates arising from affixation, and described as either assimilated or concatenated, were matched to fake geminates arising from sequences ...

An important challenge in the process of tracking and detecting the dissemination of misinformation is to understand the gap in the political views between people that engage with the so called ”fake news”. A possible factor responsible for this gap is opinion polarization, which may prompt the general public to classify content that they disagree or want to discredit as fake. In this work, we ...

The problem of fake news has gained a lot of attention as it is claimed to have had a significant impact on 2016 US Presidential Elections. Fake news is not a new problem and its spread in social networks is well-studied. Often an underlying assumption in fake news discussion is that it is written to look like real news, fooling the reader who does not check for reliability of the sources or th...

Online reviews are a growing market, but it is struggling with fake reviews. They undermine both the value of reviews to the user, and their trust in the review sites. However, fake positive reviews can boost a business, and so a small industry producing fake reviews has developed. The two sides are facing an arms race that involves more and more natural language processing (NLP). So far, NLP h...

Despite its scientific and practical importance, relatively few studies have been conducted to investigate the relationship between job applicant mental abilities and faking. Some studies suggest that more intelligent people fake less because they do not have to. Other studies suggest that more intelligent people fake more because they have increased capacity to fake. Based on a model of faking...

Automatic fake news detection is a challenging problem in deception detection, and it has tremendous real-world political and social impacts. However, statistical approaches to combating fake news has been dramatically limited by the lack of labeled benchmark datasets. In this paper, we present LIAR: a new, publicly available dataset for fake news detection. We collected a decade-long, 12.8K ma...

Medical Savings Accounts (MSAs) are usually promoted as a demand-management tool that gives consumers incentives to economize on medical expenses. "Making Health Spending Work" takes the concept one step further and shows how MSAs can be used to design a publicly funded system that incorporates market dynamics. MSAs can bring efficiency-enhancing incentives to the supply side, creating consumer...