Computational fact checking from knowledge networks

Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation

Bootstrapping Trust in Online Dating: Social Verification of Online Dating Profiles

Online dating is an increasingly thriving business which boasts billion-dollar revenues and attracts users in the tens of millions. Notwithstanding its popularity, online dating is not impervious to worrisome trust and privacy concerns raised by the disclosure of potentially sensitive data as well as the exposure to self-reported (and thus potentially misrepresented) information. Nonetheless, little research has, thus far, focused on how to enhance privacy and trustworthiness. In this paper, we report on a series of semi-structured interviews involving 20 participants, and show that users are significantly concerned with the veracity of online dating profiles. To address some of these concerns, we present the user-centered design of an interface, called Certifeye, which aims to bootstrap trust in online dating profiles using existing social network data. Certifeye verifies that the information users report on their online dating profile (e.g., age, relationship status, and/or photos) matches that displayed on their own Facebook profile. Finally, we present the results of a 161-user Mechanical Turk study assessing whether our veracity-enhancing interface successfully reduced concerns in online dating users and find a statistically significant trust increase.Comment: In Proceedings of Financial Cryptography and Data Security (FC) Workshop on Usable Security (USEC), 201

Designing an Intelligent User Interface for Preventing Phishing Attacks

Part 3: Workshop on Handling Security, Usability, User Experience and Reliability in User-Centered Development ProcessesInternational audienceMost phishing sites are simply copies of real sites with slight features distorted or in some cases masqueraded. This property of phishing sites has made them difficult for humans and various anti-phishing techniques to detect. Also, the attacker community has proved itself able to quickly adapt to anti-phishing measures, mainly warning messages to help limit the effectiveness of phishing attacks and protect unsuspecting users. Despite the notable advances made in the last years by the active warning messages for phishing, this attack remains one of the most effective. In this paper we propose an intelligent warning message mechanism, that might limit the effectiveness of phishing attacks and that might increase the user awareness about related risks. It implements an intelligent behavior that, besides warning the users that a phishing attack is occurring, explains why the specific suspect site can be fraudulent

The Decision to Access Patient Information From a Social Media Site: What Would You Do?

PURPOSE: The current study examined the prevalence with which healthcare providers use a social media site account (e.g., Facebook), the extent to which they utilize social media sites in clinical practice, and their decision-making process after accessing patient information from a social media site. METHODS: Pediatric faculty and trainees from a medical school campus were provided a social media site history form and seven fictional social media site adolescent profile vignettes that depicted concerning information. Participants were instructed to rate their personal use and beliefs about social media sites and to report how they would respond if they obtained concerning information about an adolescent patient from their public social media site profile. RESULTS: Healthcare providers generally believed it not to be an invasion of privacy to conduct an Internet/social media site search of someone they know. A small percentage of trainees reported a personal history of conducting an Internet search (18%) or a social media site search (14%) for a patient. However, no faculty endorsed a history of conducting searches for patients. Faculty and trainees also differed in how they would respond to concerning social media site adolescent profile information. CONCLUSIONS: The findings that trainees are conducting Internet/social media site searches of patients and that faculty and trainees differ in how they would respond to concerning profile information suggest the need for specific guidelines regarding the role of social media sites in clinical practice. Practice, policy, and training implications are discussed