Social Media and the Scourge of Visual Privacy Online privacy has become immensely important with the growth of technology and the expansion of communication. Social Media Networks have risen to the forefront of current communication trends. With the current trends in social media, the question now becomes how can we actively protect ourselves on these platforms? Users of social media networks share billions of images a day. Whether intentional or unintentional, users tend to share private information within these images. In this study, we investigate (1) the usersxe2x80x99 perspective of privacy, (2) pervasiveness of privacy leaks on Twitter, and (3) the threats and dangers on these platforms. In this study, we incorporate techniques such as text analysis, analysis of variance, and crowdsourcing to process the data received from these sources. Based on the results, the participantsxe2x80x99 definitions of privacy showed overlap regardless of age or gender identity. After looking at the survey results, most female participants displayed a heightened fear of dangers on social media networks because of threats in the following areas: assets and identity. When the participants were asked to rank the threats on social media, they showed a high concern for burglary and kidnapping. We find that participants need more education about the threats of visual content and how these privacy leaks can lead to physical, mental, and emotional danger.

Detecting Cyberbullying and Cyberaggression in Social Media Cyberbullying and cyberaggression are increasingly worrisome phenomena affecting people across all demographics. More than half of young social media users worldwide have been exposed to such prolonged andor coordinated digital harassment. Victims can experience a wide range of emotions, with negative consequences such as embarrassment, depression, isolation from other community members, which embed the risk to lead to even more critical consequences, such as suicide attempts.  :66,this work, we take the first concrete steps to understand the characteristics of abusive behavior in Twitter, one of todayu0027s largest social media platforms. We analyze 1.2 million users and 2.1 million tweets, comparing users participating in discussions around seemingly normal topics like the NBA, to those more likely to be haterelated, such as the Gamergate controversy, or the gender pay inequality at the BBC station. We also explore specific manifestations of abusive behavior, i.e., cyberbullying and cyberaggression, in one of the haterelated communities (Gamergate). We present a robust methodology to distinguish bullies and aggressors from normal Twitter users by considering text, user, and networkbased attributes. Using various stateoftheart machine learning algorithms, we classify these accounts with over 90% accuracy and AUC. Finally, we discuss the current status of Twitter user accounts marked as abusive by our methodology, and study the performance of potential mechanisms that can be used by Twitter to suspend users in the future.