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This study aims to analyze whether average video watch time or click-through rates (CTR) on YouTube videos are more closely associated with high numbers of views per subscriber using linear regressions.

In 2018, YouTube began releasing CTR data to its video creators. Since 2012, YouTube has emphasized how it favors watch time over clicks in its recommendations to viewers. To the best of the author’s knowledge, this is the first academic study looking at that CTR data to test what matters more for views on YouTube. Is watch time or CTR more important to getting views on YouTube?

The author analyzed new video releases on YouTube. This paper finds almost no or limited evidence that higher percent audience retention or total average watch time per view, respectively, are associated with more views on YouTube. Instead, videos with higher CTR got significantly more views.

The author knows no other study that tests the relative importance of CTR or watch time per view in predicting views for new videos on YouTube.

The purpose of this paper is to explore the emotions reported by a group of student teachers (STs) after viewing their own teaching videos and those of their peers, as well as the reasons for those emotions. It also investigated the perceived influence of the STs’ emotions on their learning from the videos.

The case study involved 12 STs, and was situated in the context of a science methods course on a postgraduate teaching diploma program. The emotions associated with watching different types of video materials were investigated using a variety of data-collection methods, including written surveys, student-generated metaphors, and interviews. The emotion labels/words (e.g. horrible, joyful) and metaphors the STs used to describe their video-viewing experience, as well as the reasons for their emotions, were analyzed. The perceived influence of the participants’ emotions on their learning from the different types of video material was also analyzed qualitatively.

The findings suggested that most of the STs experienced negative emotions when viewing their own videos, whereas all of them reported positive emotions when viewing their peers’ videos. Distinct groups of STs displaying similar emotions while viewing the different video materials were distinguished. Their characteristics and the reasons for their emotions were identified. Analysis of the perceived influence of emotions suggested that they exert differential influences on learning from video materials, with the negative emotions associated with viewing one’s own videos reported to hinder such learning in most cases.

This study represents one of the few attempts to investigate the emotions related to STs’ video-viewing experience. The case study problematizes the lack of attention to the emotions associated with ST’s video-viewing experience in existing scholarship and highlights the fact that research findings on in-service teachers’ emotions associated with viewing different types of video material might not be transferable to novice teachers. The identification of distinct groups of STs who experience particular emotions when viewing different types of video material, as well as the differing perceived influence of those emotions on their learning, has implications for the effective use of videos to enhance learning in initial teacher education.

YouTube allows its users to upload and view videos on its platform. YouTube provides notification to the subscribers whenever a channel uploads a new video thereby making the channel subscribers the potential viewers of the video. And thus, they are the first to come to know about any new offering. But later on, the view count also increases due to virality, that is, mass sharing of the content by the users on different social media platforms similar to word-of-mouth in the field of marketing. Therefore, the purpose of this paper is to examine different diffusion patterns as they can help to inflate traffic and generate revenue.

YouTube's view count grows majorly through virality. The pattern of view count growth has generally been considered unimodal in most of the available research in the field of YouTube. In the present work, the growth process due to views through the subscribers and views due to word-of-mouth (virality) is presented. Considering that the impact of virality in view count growth comes later in the video life cycle; the viewing patterns of both the segments have been mathematically modeled; independently.

Different models have been proposed to capture the view count growth pattern and how the impact of virality changes the view count growth curve and thereby results in a multimodal curve structure. The proposed models have been verified on various view count data sets of YouTube videos using SPSS (Statistical Package for the Social Sciences), and their ranks have been determined using a weighted criteria–based approach. The results obtained clearly depict the presence of many modes in the life cycle of view counts.

Till now, the literature is evident of the video life cycle following a bell shape curve. This study claims that the initial thrust is by subscribers and then the contribution in the view count by people watching via word-of-mouth comes into picture and brings in another hump in the growth curve.

YouTube's vast and engaged user base makes it central to firms' digital marketing effort. With extant studies focusing on viewers' post-view engagement behavior, however, research into what motivates viewers to click on and watch YouTube videos is scarce. This study investigates the implications of marketers' video optimization practices for video views on YouTube.

The study employed a data set of videos (N = 4,398) gathered by scraping YouTube's trending list. Using a combination of text and sentiment analysis, the study measured four video optimization practices: information content of video titles, emotional intensity of video titles, information content of video descriptions and volume of video tags. It then analyzed the effect of these video optimization practices on video views.

The study finds that greater availability of information in video titles is negatively associated with video views, whereas intensity of negative emotional sentiment in video titles is positively associated with video views. Further, greater availability of information in video descriptions is positively associated with video views. Finally, an inverted U-shaped relationship is found between volume of video tags and video views. Up to 17 video tags can contribute to more video views; however, beyond 17 tags, the relationship turns negative.

This study investigates the effect of marketers' video optimization practices on video views. While extant studies mainly focus on viewers' post-view engagement behavior, such as liking, commenting on and sharing videos, this study examines video views. Similarly, extant studies investigate videos' internal content, while this study investigates elements of the video metadata.

The purpose of this study/paper is to propose a mathematical model that is able to predict the future popularity based on the view count of a particular YouTube video. Since the emergence of video-sharing sites from early 2005, YouTube has been pioneering in its performance and holds the largest share of internet traffic. YouTube plays a significant role in popularizing information on social network. For all social media sites, viewership is an important and vital component to measure diffusion on a video-sharing site, which is defined in terms of the number of view counts. In the era of social media marketing, companies demand an efficient system that can predict the popularity of video in advance. Diffusion prediction of video can help marketing firms and brand companies to inflate traffic and help the firms in generating revenue.

In the present work, viewership is studied as an important diffusion-affecting parameter pertaining to YouTube videos. Primarily, a mathematical diffusion model is proposed to predict YouTube video diffusion based on the varying situations of viewership. The proposal segregates the total number of viewers into two classes – neoterics viewers, i.e. viewers those viewing a video on a direct basis, and followers, i.e. viewers those watching under the influence.

The approach is supplemented with numerical illustration done on the real YouTube data set. Results prove that the proposed approach contributes significantly to predict viewership of video. The proposed model brings predicted viewership and its classification highly close to the true value.

Thereby, a behavioral rationale for the modeling and quantification is offered in terms of the two varied and yet connected classes of viewers – “neoterics” and “followers.”

The purpose of this study is to investigate visual comprehension in memory for 360-degree video advertisements amongst adolescents under single and repeated viewing conditions.

This study explored visual comprehension in memory for 360-degree video advertisements using the theoretical assumptions of the social psychology theory of social information processing by Wyer (2003). The authors conducted two experiments over a timeline of three months. In the first experiment, participants watched the 360-degree video advertisement once, and after one week, the same set of participants watched the same advertisement again. The theoretical assumptions in the comprehension unit were used to design the experiments and to explore visual comprehension in memory for 360-degree video advertisements. The data were collected using surveys and interviews through an experimental research design approach. NVivo software was used to analyse the data.

This study found that while female participants were able to comprehend colours in the visuals better, male participants were better able to comprehend facial expressions presented in the visuals. Further, both female and male participants were able to comprehend locations within the advertisement visuals. It was found that participants understood the plot or the story of the advertisement better after the second viewing than after the first viewing.

The two main contributions from this study are as follows: from a theoretical perspective, the application of a social psychology theory for the advertising sector enables us to gather more insights about the social cognition stages of a human mindset such as information retrieval, judgement, decision making, goal stimulation and short- and long-term memory. In doing so, this study not only explored adolescents' visual comprehension memory of 360-degree video advertisements, but it also contributed to the theory of social information processing by Wyer (2003) by exploring consumer visual comprehension memory. From a practical perspective, the findings of this study provide a solid foundation for future advertising firms or agencies, marketers, and salespeople on how to design effective advertisements using 360-degree video versions in a way that appeals to consumer visual memory.

This paper can be considered as amongst the first studies which combine social psychology with advertising to investigate visual comprehension memory for 360-degree video advertisements amongst adolescents.

The purpose of this paper is to seek reasons for some videos going viral over YouTube (a type of social media platform).

Using YouTube APIs (Application Programming Interface) and Webometrics analyst tool, the authors collected data on about 100 all-time-most-viewed YouTube videos and information about the users associated with the videos. The authors constructed and tested an empirical model to understand the relationship among users’ social and non-social capital (e.g. User Age, Gender, View Count, Subscriber, Join Date, Total Videos Posted), video characteristics (Post Date, Duration, and Video Category), external network capital (in-links and hit counts), and Virality (Likes, Dislikes, Favorite Count, View Count, and Comment Count). Partial least square and Webometric analysis was used to explore the association among the constructs.

Among other findings, the results showed that popularity of the videos was not only the function of YouTube system per se, but that network dynamics (e.g. in-links and hits counts) and offline social capital (e.g. fan base and fame) play crucial roles in the viral phenomenon, particularly view count.

The authors for the first time constructed and tested an empirical model to find out the determinants of viral phenomenon over YouTube.

NHS Direct Digital was available to almost exactly the same number of users in both Hull and London via two different transmission DiTV companies: Kingston Interactive Television (KIT) and HomeChoice. This paper employs metrics based on server generated logs to compare use and user differences between the two services. Server logs that record user activity on a real‐time and continuous basis were made available and used to make comparisons between the two services. The data were collected for both services over a similar period, February 2002 to May 2002. During this period the NHS Direct Digital service was visited by approximately 3,000 people and more than 5,000 NHS Direct videos were viewed. Making the study probably the largest analysis of health videos ever conducted.

Reports on a qualitative study exploring a highly innovative digital TV pilot service. Focus groups of medical and health information professionals, “condition‐specific” subjects and “general interest” volunteers were recruited to obtain views about the videos generally, in terms of their content and presentation. Issues such as terminology used and the appropriateness of using video to deliver various types of information were also explored; the latter in the light of log statistics indicating relatively low use of videos as compared to text‐based services. Results indicated that those who used the services tended to be avid seekers of information, who saw the service as a first port of call to obtain general information for wider consultation later. Differences emerged between medical professionals and the lay public regarding the use of language and involvement of patients in the videos. Text was regarded as a better medium for conveying some types of information, such as simple facts that might need to be consulted on a regular basis.

My original intention in writing this discussion chapter was to conduct a fine-grained comparison and contrast of what the contributors had to say about several aspects of making and using video in teacher education. However, my initial notes indicated that I would have nothing different and not much more to say than Ladewski (1996) already said in her comparison of four video-based teacher education programs. Furthermore, continued study of the chapters underscored the fact that seeming disagreements were mostly reflections of differences in the authors’ target learners and program goals, not actual disagreements about what or how video should be used.