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Richard Han

Publications and source records attributed to Richard Han.

28 records · Page 2Linked to original sources

Prediction of Cyberbullying Incidents on the Instagram Social Network

Cyberbullying is a growing problem affecting more than half of all American teens. The main goal of this paper is to investigate fundamentally new approaches to understand and automatically detect and predict incidents of cyberbullying in Instagram, a media-based mobile social network. In this work, we have collected a sample data set consisting of Instagram images and their associated comments. We then designed a labeling study and employed human contributors at the crowd-sourced CrowdFlower website to label these media sessions for cyberbullying. A detailed analysis of the labeled data is then presented, including a study of relationships between cyberbullying and a host of features such as cyberaggression, profanity, social graph features, temporal commenting behavior, linguistic content, and image content. Using the labeled data, we further design and evaluate the performance of classifiers to automatically detect and pre- dict incidents of cyberbullying and cyberaggression.

cs.IR↗

Detection of Cyberbullying Incidents on the Instagram Social Network

Cyberbullying is a growing problem affecting more than half of all American teens. The main goal of this paper is to investigate fundamentally new approaches to understand and automatically detect incidents of cyberbullying over images in Instagram, a media-based mobile social network. To this end, we have collected a sample Instagram data set consisting of images and their associated comments, and designed a labeling study for cyberbullying as well as image content using human labelers at the crowd-sourced Crowdflower Web site. An analysis of the labeled data is then presented, including a study of correlations between different features and cyberbullying as well as cyberaggression. Using the labeled data, we further design and evaluate the accuracy of a classifier to automatically detect incidents of cyberbullying.

cs.SI↗

A Comparison of Common Users across Instagram and Ask.fm to Better Understand Cyberbullying

This paper examines users who are common to two popular online social networks, Instagram and Ask.fm, that are often used for cyberbullying. An analysis of the negativity and positivity of word usage in posts by common users of these two social networks is performed. These results are normalized in comparison to a sample of typical users in both networks. We also examine the posting activity of common user profiles and consider its correlation with negativity. Within the Ask.fm social network, which allows anonymous posts, the relationship between anonymity and negativity is further explored.

cs.SI↗

Towards Understanding Cyberbullying Behavior in a Semi-Anonymous Social Network

Cyberbullying has emerged as an important and growing social problem, wherein people use online social networks and mobile phones to bully victims with offensive text, images, audio and video on a 247 basis. This paper studies negative user behavior in the Ask.fm social network, a popular new site that has led to many cases of cyberbullying, some leading to suicidal behavior.We examine the occurrence of negative words in Ask.fms question+answer profiles along with the social network of likes of questions+answers. We also examine properties of users with cutting behavior in this social network.

cs.SI↗

Results from a Practical Deployment of the MyZone Decentralized P2P Social Network

This paper presents MyZone, a private online social network for relatively small, closely-knit communities. MyZone has three important distinguishing features. First, users keep the ownership of their data and have complete control over maintaining their privacy. Second, MyZone is free from any possibility of content censorship and is highly resilient to any single point of disconnection. Finally, MyZone minimizes deployment cost by minimizing its computation, storage and network bandwidth requirements. It incorporates both a P2P architecture and a centralized architecture in its design ensuring high availability, security and privacy. A prototype of MyZone was deployed over a period of 40 days with a membership of more than one hundred users. The paper provides a detailed evaluation of the results obtained from this deployment.

cs.CR↗

An Empirical Study of Spam and Prevention Mechanisms in Online Video Chat Services

Recently, online video chat services are becoming increasingly popular. While experiencing tremendous growth, online video chat services have also become yet another spamming target. Unlike spam propagated via traditional medium like emails and social networks, we find that spam propagated via online video chat services is able to draw much larger attention from the users. We have conducted several experiments to investigate spam propagation on Chatroulette - the largest online video chat website. We have found that the largest spam campaign on online video chat websites is dating scams. Our study indicates that spam carrying dating or pharmacy scams have much higher clickthrough rates than email spam carrying the same content. In particular, dating scams reach a clickthrough rate of 14.97%. We also examined and analysed spam prevention mechanisms that online video chat websites have designed and implemented. Our study indicates that the prevention mechanisms either harm legitimate user experience or can be easily bypassed.

cs.CR↗

MyZone: A Next-Generation Online Social Network

This technical report considers the design of a social network that would address the shortcomings of the current ones, and identifies user privacy, security, and service availability as strong motivations that push the architecture of the proposed design to be distributed. We describe our design in detail and identify the property of resiliency as a key objective for the overall design philosophy. We define the system goals, threat model, and trust model as part of the system model, and discuss the challenges in adapting such distributed frameworks to become highly available and highly resilient in potentially hostile environments. We propose a distributed solution to address these challenges based on a trust-based friendship model for replicating user profiles and disseminating messages, and examine how this approach builds upon prior work in distributed Peer-to-Peer (P2P) networks.

cs.SI↗

A Construction of the "2221" Planar Algebra

In this paper, we construct the "2221" subfactor planar algebra by finding it as a subalgebra of the graph planar algebra of its principal graph. In particular, we give a presentation of the "2221" subfactor planar algebra consisting of generators and relations. As a corollary, we have a planar algebra proof of the existence of a subfactor with principal graph "2221". To show the subfactor property, we use the jellyfish algorithm for evaluating closed diagrams. Lastly, we show uniqueness up to conjugation of "2221".

math.OA↗

SafeVchat: Detecting Obscene Content and Misbehaving Users in Online Video Chat Services

Online video chat services such as Chatroulette, Omegle, and vChatter that randomly match pairs of users in video chat sessions are fast becoming very popular, with over a million users per month in the case of Chatroulette. A key problem encountered in such systems is the presence of flashers and obscene content. This problem is especially acute given the presence of underage minors in such systems. This paper presents SafeVchat, a novel solution to the problem of flasher detection that employs an array of image detection algorithms. A key contribution of the paper concerns how the results of the individual detectors are fused together into an overall decision classifying the user as misbehaving or not, based on Dempster-Shafer Theory. The paper introduces a novel, motion-based skin detection method that achieves significantly higher recall and better precision. The proposed methods have been evaluated over real world data and image traces obtained from Chatroulette.com.

cs.CR↗

Intrusions into Privacy in Video Chat Environments: Attacks and Countermeasures

Video chat systems such as Chatroulette have become increasingly popular as a way to meet and converse one-on-one via video and audio with other users online in an open and interactive manner. At the same time, security and privacy concerns inherent in such communication have been little explored. This paper presents one of the first investigations of the privacy threats found in such video chat systems, identifying three such threats, namely de-anonymization attacks, phishing attacks, and man-in-the-middle attacks. The paper further describes countermeasures against each of these attacks.

cs.CR↗