Exploring the flaming scenario on youtube within the Malaysian context

One of the major acts of cyber-bullying in today’s Internet era is flaming. Flaming refers to the use of offensive language such as swearing and insulting as well as posting hateful comments through an online medium. In this study, the act of flaming was explored in the context of social media, particularly YouTube. The research aims to understand 'individuals' in posting hateful comments on YouTube and to classify ‘flaming’ comments posted on YouTube videos in Malaysia. The Uses and Gratifications theory (UGT) was used to explain the commenters' satisfaction obtained through the flaming activity and the motivation to flame on the site. The methodology in this study were in-depth interviews and content analysis. Ten flamers were interviewed to understand their motivation to flame on YouTube. As for content analysis, one video was chosen for each top five out of fifteen categories available on YouTube. The categories were entertainment, film and animation, news and politics, comedy and people and blogs, with at least 100,000 views and a minimum of 100 comments and analyzed thematically. It can be concluded that the motivation to flame in Malaysia includes anonymity, norm, aspect of entertainment, being defensive and so on. As for the comments' classifications for content analysis, the results show that the most prominent types of comments found on Malaysian videos are political attack and racial attack. Other subcategories include name calling, insult, criticism, sexual attack, sarcasm, inter-country attack, speculation, defamation, comparison, sexism, religious attack, threaten, homophobic, stereotype, inter-state attack, sedition, defensive and comments that are off-topic. This study contributes to the usage of UGT in a new perspective which is gratification sought through negativity (flaming). This study also contributes practically in the enrichment of the data on flaming for the concerning parties such as Malaysian Communications and Multimedia Commission and Cyber Security Malaysia

An analysis on a YouTube-like UGC site with enhanced social features

YouTube-like User Generated Content (UGC) sites are nowadays entertaining over a billion people. Resource provision is essential for these giant UGC sites as they allow users to request videos from a potentially unlimited selection in an asynchronous fashion. Still, the UGC sites are seeking to create new viewing patterns and social interactions that would engage and attract more users and complicate the already rigorous resource provision problem. In this paper, we seek to combine these two tasks by leveraging social features to provide the reference for resource provision. To this end, we conduct an extensive measurement and analysis of BiliBili, a YouTube-like UGC site with enhanced social features including user following, chat replay, and virtual money donation. Based on datasets that capture the complete view of BiliBili-containing over 2 million videos and over 28 million users-we characterize its video repository and user activities, we demonstrate the positive reinforcement between on-line social behavior and upload behavior, we propose graph models that reveal user relationships and high-level social structures, and we successfully apply our findings to build machine-learnt classifiers to identify videos that will need priority in resource provision