FROM FRAMING TO FLAMING IN THE CROSS-THEOLOGICAL DEBATE: HOW ARE CHRISTIAN PRINCE’S COMMENTARIES REPRESENTED THE QUR’AN ON YOUTUBE?

Christian Prince’s (CP) presence on YouTube opened a new chapter in Christian opposition actors who act as cross-theological debaters between Muslims and Christians who, for the previous two decades, were only dominated by Muslims. Through the narratives on YouTube, this Christian apologist tries to convince the public that the Qur’an contains contradictory statements as the holy book for Muslims. In response to such an issue, this research aims to investigate the construction of CP’s interpretation, which highlights the authenticity of the Qur’an. Qualitative content and thematic analyses and the framing approach developed by William A. Gamson were employed. Findings suggest that the representation of CP’s understanding of the Qur’an verses uses a decontextualization approach. Also, the vast knowledge of the Arabic language and literary translations further strengthen the narratives to convince the public of the allegations. However, instead of considering the historical context in understanding the scientific meaning of the Qur’an, this Christian apologist uses literal meaning as a framing device. This phenomenon has shown that cross-theological debates only provoke persistent inter-religious hatred and resentment. Therefore, such debates are inclined to trigger the propaganda of religious extremists

Social Dynamics in Online Cultural Fields

In spite of a long literature on online communities and electronic networks, little theoretical work has been done on understanding a recent online phenomenon: user-generated content (UGC) platforms. This paper proposes an analytical lens for the study of social dynamics on UGC platforms. Drawing on Bourdieu\u27s concepts of field and capital, we introduce the notion of online cultural field and investigate which characteristics of agents and their contribution behavior produce status distinctions in these fields. These characteristics are then placed in a framework which attempts to address how capital is produced, reproduced and transformed in online cultural fields and how these processes help us understand the evolution of these fields. We briefly review how we will follow this theoretical model with an empirical investigation

A Network View of Social Media Platform History: Social Structure, Dynamics and Content on YouTube

Social media sites are prone to change from many internal and external causes, yet it is difficult to directly explore their histories in terms of the content itself. Search and browsing features are biased toward new and paid content, archives are difficult to navigate systematically, and their scale makes any observations challenging to contextualize. Here, we present results of an ongoing study of YouTube’s history (currently with more than 76 million videos) using a combination of iterative browsing, network crawling and clustering within and across time periods. Through this method, we are able to identify historical patterns in YouTube\u27s content related to internal and external events. Our approach thus illustrates an adaptation of network analysis for understanding genre evolution in the histories of social media platforms

Network Analysis of Recurring YouTube Spam Campaigns

As the popularity of content sharing websites such as YouTube and Flickr has increased, they have become targets for spam, phishing and the distribution of malware. On YouTube, the facility for users to post comments can be used by spam campaigns to direct unsuspecting users to bogus e-commerce websites. In this paper, we demonstrate how such campaigns can be tracked over time using network motif profiling, i.e. by tracking counts of indicative network motifs. By considering all motifs of up to five nodes, we identify discriminating motifs that reveal two distinctly different spam campaign strategies. One of these strategies uses a small number of spam user accounts to comment on a large number of videos, whereas a larger number of accounts is used with the other. We present an evaluation that uses motif profiling to track two active campaigns matching these strategies, and identify some of the associated user accounts

Deepfakes on Twitter: Which Actors Control Their Spread?

The term deepfake was first used in a Reddit post in 2017 to refer to videos manipulated using artificial intelligence techniques and since then it is becoming easier to create such fake videos. A recent investigation by the cybersecurity company Deeptrace in September 2019 indicated that the number of what is known as fake videos had doubled in the last nine months and that most were pornographic videos used as revenge to harm many women. The report also highlighted the potential of this technology to be used in political campaigns such as in Gabon and Malaysia. In this sense, the phenomenon of deepfake has become a concern for governments because it poses a short-term threat not only to politics, but also for fraud or cyberbullying. The starting point of this research was Twitter’s announcement of a change in its protocols to fight fake news and deepfakes. We have used the Social Network Analysis technique, with visualization as a key component, to analyze the conversation on Twitter about the deepfake phenomenon. NodeXL was used to identify main actors and the network of connections between all these accounts. In addition, the semantic networks of the tweets were analyzed to discover hidden patterns of meaning. The results show that half of the actors who function as bridges in the interactions that shape the network are journalists and media, which is a sign of the concern that this sophisticated form of manipulation generates in this collective

The key is not to forget to be awesome: Identifying narratives in an online community

As online communities emerge in different settings all over the web, they continue to develop different ways to communicate online and to encourage participation in their activities. Scholars have proposed that one of the ways in which these communities do so is through the use of narratives. A case study was done on an open online community to establish if online communities develop narratives, what kind of narratives, and if these influence participation. This paper contains the analysis of the identifiable narratives that are useful to promote culture and participation and proposes three types of narratives that are more effective to do so. Implications of such findings and proposed future research are discussed

YouTube Children’s Videos: Development of a Genre under Algorithm

YouTube children’s video has been claimed to have a preponderance of violent, disturbing or otherwise in-appropriate content. To assess this claim, we conduct a content analysis of a sample of children’s videos published between January 2016 and December 2018. Our analysis reveals an evolving ecosystem involving a variety of production modes and messages which nonetheless bears the heavy imprint of the algorithm-centered commercial incentives of marketing to children and attracting YouTube advertising. Hence, while content formerly causing public concern appears to be effectively policed at this juncture, algorithmic incentives do appear to distort children’s content in potentially unhealthy ways

COVID-19 Information on YouTube in the Early Pandemic

As people sheltered globally during the COVID-19 pandemic, many YouTube videos and channels pivoted to providing COVID-19 information. But were these videos helpful and constructive or did they undermine official public health messaging? This paper addresses these questions through a mixed methods study of COVID-19 videos on YouTube produced from January to May 2020. We find that a preponderance of YouTube COVID-19 videos either came from major news studio outlets or offered official public health communication. While YouTube moved quickly against obvious false messages, other more subtle ones still managed to leak through. Medical information channels presented conflicting information at times, reflecting factors such as medical uncertainties, political currents, and audience pressures associated with uncertain information around a novel pandemic