Is there negative social influence?: disentangling effects of dissimilarity and disliking on opinion shifts.

Empirical studies are inconclusive about the underlying mechanisms that shape the interrelated dynamics of opinions and interpersonal attraction. There is strong evidence that others whom are liked have a positive influence on opinions and similarities induce attraction (homophily). We know less about "negative" mechanisms concerning whether disliked others induce shifts away from consensus (negative influence), whether large differences (dissimilarity) generate distancing, and whether dissimilarities induce disliking (heterophobia). This study tests discriminating hypotheses about the presence of positive and negative mechanisms in controlled experiments involving dyadic interactions. Results confirm the presence of homophily, do not support the existence of negative social influence, and show a robust positive linear relationship between opinion distance and opinion shifts. This implies that contact might provide the largest push towards consensus in case of large initial differences

Factors influencing the popularity of YouTube videos and users’ decisions to watch them

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.YouTube has substantial impact on modern society as the second most popular website in the world. Despite its sustained popularity, little is known about which types of video are most viewed and the reasons why people choose to watch them. This research critically analyses the sample of videos provided by the YouTube API, then uses the metrics associated with these videos to help assess which types of YouTube video are popular. It also harnesses a questionnaire of mainly UK teacher education graduate YouTube users to investigate which factors influence decisions to watch YouTube videos. This was a convenience sample selected to achieve a high response rate, which it achieved (81%), minimising non-response bias. The video lists provided by the YouTube API were not random samples but contained a wide range of types of video (including both popular and unpopular), except that older videos were avoided. There were substantial differences between categories in the average properties of the videos returned and the proportion of videos returned on multiple days. The most popular categories from the YouTube metadata collected based on average view counts are varied: From TV, Best of, Animation and How-to. Cause-based video categories tended to be unpopular. Video popularity did not seem to be affected by video duration, on average. Users are more likely to interact with (comment, like, dislike) videos that are useful or supporting in some way. Videos that are interacted with more are not always more popular, with subject content affecting this relationship. In addition, high view counts associated with fewer likes, dislikes and comments per view, suggesting that indicators of popularity may not attract new viewers. The most popular categories with survey respondents were slightly different, partly reflecting their educational background (e.g., Education videos), and there were some (stereotypical) gender differences in the most popular categories. Respondents rarely believed that they were influenced by a video’s popularity or evidence of other users’ reactions to it when deciding to watch the video. Instead, they were most likely to be influenced by content-related factors, such as a video’s title and thumbnail picture. Despite previous research showing that people can be influenced by the opinions and watching habits of others, respondents claimed to be little influenced by this. Nevertheless, they frequently reported watching videos posted to Facebook, possibly trusting the person that posted the video. Thus, despite extensive discussion of various forms of viral information spreading, content, rather than popularity, is king in YouTube, although online word-of-mouth sharing through trusted relationships is also important. The main limitations of this research are that the data used may not be representative of YouTube and all UK YouTube users overall, so the conclusions should be interpreted cautiously