The hookah pipe is an ancient tool for smoking tobacco and is a growing public health concern at the global level. YouTube is a website that allows its members to post videos for people to watch and to share comments about the videos in an online forum. The purpose of the study was to investigate the types of videos about hookah on YouTube, their popularity, and the demographics of those who po...

The Pareto principle (also known as the 80/20 rule) states that about 80% of the consequences are created by 20% of the causes. In this paper we describe the distribution of several aspects of YouTube, a website used for online video sharing, to see if the Pareto principle applies to these aspects. These aspects include the views and comments of videos, and the videos uploaded and comments post...

What makes content go viral? Which videos become popular and why others don’t? Such questions have elicited significant attention from both researchers and industry, particularly in the context of online media. A range of models have been recently proposed to explain and predict popularity; however, there is a short supply of practical tools, accessible for regular users, that leverage these th...

EventNet is a large-scale video corpus and event ontology consisting of 500 events associated with event-specific concepts. In order to improve the quality of the current EventNet, we conduct the following steps and introduce EventNet version 1.1: (1) manually verify the correctness of event labels for all videos; (2) remove the YouTube user bias by limiting the maximum number of videos in each...

Understanding content popularity growth on Online Social Networks (OSNs) is of great importance to Internet service providers, content creators and online marketers. However, most previous studies of OSNs are based on static views of the system, thus neglecting the temporal evolution of the network, and a possible correlation with content popularity growth. Moreover, previous analyses also grea...

Nowadays, people capture, edit and share more and more home videos. Devices with video capturing capability and services for video sharing and editing are becoming increasingly popular. This study was conducted to chart in more detail what users currently do with their home videos, and what their desires, problems and needs are. The results of an Internet-based survey learned that home videos h...

We present a new system for video auto tagging which aims at correcting and completing the tags provided by users for videos uploaded on the Internet. Unlike most existing systems, we do not learn any tag classifiers or use the questionable textual information to compare our videos. We propose to compare directly the visual content of the videos described by different sets of features such as B...

Recently, deep neural network has shown promising performance in face image recognition. The inputs of most networks are face images, and there is hardly any work reported in literature on network with face videos as input. To sufficiently discover the useful information contained in face videos, we present a novel network architecture called input aggregated network which is able to learn fixe...