Who watches (and shares) what on youtube? and when?

Abstract

By combining multiple social media datasets, it is possible to gain insight into each dataset that goes beyond what could be obtained with either individually. In this paper we combine user-centric data from Twitter with video-centric data from YouTube to build a rich picture of who watches and shares what on YouTube. We study 87K Twitter users, 5.6 million YouTube videos and 15 million video sharing events from user-, video-and sharing-eventcentric perspectives. We show that features of Twitter users correlate with YouTube features and sharing-related features. For example, urban users are quicker to share than rural users. We find a superlinear relationship between initial Twitter shares and the final amounts of views. We discover that Twitter activity metrics play more role in video popularity than mere amount of followers. We also reveal the existence of correlated behavior concerning the time between video creation and sharing within certain timescales, showing the time onset for a coherent response, and the time limit after which collective responses are extremely unlikely. Response times depend on the category of the video, suggesting Twitter video sharing is highly dependent on the video content. To the best of our knowledge, this is the first large-scale study combining YouTube and Twitter data, and it reveals novel, detailed insights into who watches (and shares) what on YouTube, and when.

Understanding Popularity, Reputation, and Social Influence in the Twitter Society

“…Our perspective measuring popularity through the amount of followers and reputation through in‐coreness is extensible to other directed social networking sites such as Instagram or Youtube, and thus future research can explore if other sites follow similar mechanics as the ones we revealed here. Furthermore, fine grained takes on user behavior can study important aspects of popularity, for example, on different classes of accounts related to companies and promotional content (Abisheva et al, ), or on linguistic and sentiment signals in popularity growth (Niven et al, ).…”

“…As explained more in detail in the following section, we mark a user as active, if they posted a tweet since April 1, 2016, approximately three months before the data retrieval date in 2016. Social influence as average retweet rate in 2016: We quantify the social influence of a user as the average of the amount of retweets received by the tweets of each user that we captured in the 2016 social influence data set. This metric, inspired in Twitter social influence research (Abisheva, Garimella, Garcia, & Weber, ; Guille, Hacid, Favre, & Zighed, ), captures the power of a user to spread information across Twitter as a manifestation of immediate social influence, that is, the activity of other users in terms of retweets.…”

Subject matter of videos for teens on YouTube

“…While they are constructing their own identity and trying out different forms of presenting themselves, there are teenagers who create, share and disseminate videos. The content covers different subjects: social (Abisheva, Kiran-Garimella, García, & Weber, 2014), cultural (Chau, 2010), public health (Wartella, Rideout, Montague, Beaudoin-Ryan, & Lauricella, 2016), political (Días-da-Silva & Garcia, 2012) and economic issues (Ritzer & Jurgenson, 2010). Although they do not represent a large proportion of the total, some teens can also become content creators, with their own communicative practices that differ from traditional audiovisual forms (Tolson, 2010).…”

Whose Advantage? Measuring Attention Dynamics across YouTube and Twitter on Controversial Topics

“…There have also been evidences that liberal and conservative groups attract online attention in different manners. Abisheva et al (2014) focused on a set of influential Twitter users who promoted YouTube videos, and they found that conservatives tweeted more diverse topics than liberals and that conservatives shared new videos faster. Bakshy, Messing, and Adamic (2015) quantified the extent to which Facebook users were exposed to politically opposing contents, and they found that conservatives tended to seek out more cross-partisan content.…”