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...

Drug use by people is on the rise and is of great interest to public health agencies and law enforcement agencies. As found by the National Survey on Drug Use and Health, 20 million Americans aged 12 years or older consumed illicit drugs in the past few 30 days. Given their ubiquity in everyday life, drug abuse related studies have received much and constant attention. However, most of the exis...

The rapid spread of social media has brought new ways for marketers to communicate and manage brands online. Celebrity endorsement has been a popular practice in social media, however, what contributes to its effectiveness has not been fully understood. To address this issue, this study examines the effects of endorsement in social media towards brand attitude and merchandise attractiveness bas...

This paper investigates when users create profiles in different social networks, whether they are redundant expressions of the same persona, or they are adapted to each platform. Using the personal webpages of 116,998 users on About.me, we identify and extract matched user profiles on several major social networks including Facebook, Twitter, LinkedIn, and Instagram. We find evidence for distin...

Image tagging is an essential step for developing Automatic Image Annotation (AIA) methods that are based on the learning by example paradigm. However, manual image annotation, even for creating training sets for machine learning algorithms, requires hard effort and contains human judgment errors and subjectivity. Thus, alternative ways for automatically creating training examples, i.e., pairs ...

In this paper, we describe AsonMaps, a platform for collection, aggregation, visualization and analysis of near real-time, geolocated quantifiable information from a variety of heterogeneous social media outlets in order to provide emergency responders and other coordinating federal agencies not only with the means of listening to the affected population, but also to be able to incorporate this...

Social media have become dominant in everyday life during the last few years where users share their thoughts and experiences about their enjoyable events in posts. Most of these posts are related to different categories related to: activities, such as dancing, landscapes, such as beach, people, such as selfie, and animals such as pets. While some of these posts become popular and get more atte...

We examine an increasingly prevalent form of media known as micro-videos, time-constrained (typically 5-10 second) video clips commonly used on social networking sites such as Instagram and Vine. Micro-videos can be interpreted as the visual analog of a character-limited microblogs or “tweets”. An estimated 12 million micro-videos are posted to Twitter each day. The number of micro-videos produ...

Social media statistics during recent disasters (e.g. the 20 million tweets relating to ‘Sandy’ storm and the sharing of related photos in Instagram at a rate of 10/sec) suggest that the understanding and management of real-world events by civil protection and law enforcement agencies could benefit from the effective blending of social media information into their resilience processes. In this ...

Picture-taking has never been easier. We now use our phones to snap photos and instantly share them with friends, family and strangers all around the world. Consequently, we seek ways to visualize, analyze and discover concealed sociocultural characteristics and trends in this ever-growing flow of visual information. How do we then trace global and local patterns from the analysis of visual pla...