Rahat Ibn Rafiq

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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 cyberbul-lying over images in Instagram, a media-based mobile social network. To this end, we have collected a sample Instagram data set consisting(More)
As online social networks have grown in popularity, teenage users have become increasingly exposed to the threats of cyberbullying. The primary goal of this research paper is to investigate cyberbullying behaviors in Vine, a mobile based video-sharing online social network, and design novel approaches to automatically detect instances of cyberbullying over(More)
Cyberbullying is a growing problem affecting more than half of all American teens. The main goal of this paper is to study labeled cyberbullying incidents in the Instagram 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(More)
—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.(More)
This paper investigates the development of accurate and efficient classifiers to identify misbehaving users (i.e., " flashers ") in a mobile video chat application. Our analysis is based on video session data collected from a mobile client that we built that connects to a popular random video chat service. We show that prior image-based classifiers designed(More)
Collaborative computing, where co-located mobile devices collaborate to perform a large computing task has emerged as an important computing paradigm. Two key challenges in this paradigm are discovering nearby mobile devices that are willing to participate and establishing trusted connections. This paper presents a middleware layer called CoTrust that(More)
The last decade has experienced an exponential growth of popularity in online social networks. This growth in popularity has also paved the way for the threat of cyberbullying to grow to an extent that was never seen before. Online social network users are now constantly under the threat of cyberbullying from predators and stalkers. In our research paper,(More)
Cyberbullying in online social networks has become a critical problem, especially among teenagers who are social net-works' prolific users. As a result, researchers have focused on identifying distinguishing features of cyberbullying and developing techniques to automatically detect cyberbully-ing incidents. While this research has resulted in developing(More)
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(More)