Attention-grabbing news coverage : violent images of the Black Lives Matter movement and how they attract user attention on Reddit

Portrayals of violence are common in contemporary media reporting; they attract public attention and influence the reader’s opinion. In the particular context of a social movement such as Black Lives Matter (BLM), the portrayal of violence in news coverage attracts public attention and can affect the movement’s development, support, and public perception. Research on the relationship between digital news content featuring violence and user attention on social media has been scarce. This paper analyzes the relationship between violence in online reporting on BLM and its effect on user attention on the social media platform Reddit. The analysis focuses on the portrayal of violence in images used in BLM-related digital news coverage shared on Reddit. The dataset is comprised of 5,873 news articles with images. The classification of violent images is based on a VGG19 convolutional neural network (CNN) trained on a comprehensive dataset. The results suggest that what significantly affects user attention in digital news content is not the display of violence in images; rather, it is negative article titles, the news outlet’s political leanings and level of factual reporting, and platform affordances that significantly affect user attention. Thus, this paper adds to the understanding of user attention distributions online and paves the way for future research in this field

Characterizing Political Talk on Twitter: A Comparison Between Public Agenda, Media Agendas, and the Twitter Agenda with Regard to Topics and Dynamics

Social media platforms, especially Twitter, have become a ubiquitous element in political campaigns. Although politicians, journalists, and the public increasingly take to the service, we know little about the determinants and dynamics of political talk on Twitter. We examine Twitter’s issue agenda based on popular hashtags used in messages referring to politics. We compare this Twitter agenda with the public agenda measured by a representative survey and the agendas of newspapers and television news programs captured by content analysis. We show that the Twitter agenda had little, if any, relationship with the public agenda. Political talk on Twitter was somewhat stronger connected with mass media coverage, albeit following channel-specific patterns most likely determined by the attention, interests, and motivations of Twitter users

What Do They Meme? Exploring the Role of Memes as Cultural Symbols of Online Communities

Analyzing symbols shared within online communities (OCs) is essential to better understand communities’ expressed cultures. To evaluate how OCs differ in their expressed culture and analyze the effects of community rules (CR) and moderation policies (MP), we examined meme sharing of subreddit and interaction communities on Reddit. To detect memes shared within subreddits automatically, we trained a convolutional neural network and applied a feature-matching algorithm to create meme networks with components consisting of visually similar memes. Based on each community’s component composition, we created community-specific meme languages that we compared across subreddit and interaction communities. Our results show that memes can be aggregated to characteristic meme languages linked to individual OCs; yet MP and CR do not impact the homogeneity of shared memes. Based on these findings, we plan to analyze dynamically the relationship between memes and OCs, examining memes’ textual content and diving deeper into users’ individual meme languages

Collective Dynamics of Digitally Enabled Social Networks

This thesis investigates the role of technology in the collective dynamics of digitally enabled social networks. Based on a review of the historical foundation of research on crowds, collective behaviour, and collective dynamics in the social sciences and in research on complex systems, it develops a conceptualisation of collective dynamics in the context of digitally enabled social networks. This conceptualisation provides the foundation for one overarching and three subordinate research questions dedicated to different aspects of the role technology plays in understanding and managing the collective dynamics of digitally enabled social networks. The body of work comprising this dissertation is distributed across fifteen papers that contribute to these research questions

Establishing Information Quality Guidelines in Social Information Systems: Comparison and Discussion of Two Approaches

Social Information Systems (SocIS) enable many people to interact digitally and collaboratively create and share digital content. Nevertheless, the large and heterogenous SocIS communities make it challenging to ensure information quality (IQ) because members’ interpretation and evaluation of content might be very different. As a remedy, many platforms explicitly state normative IQ guidelines. Guidelines can be developed either by the community members themselves or by the platform provider (and imposed on the community). It is unclear, however, which of these two approaches members agree with more strongly and which produces the more satisficatory IQ guidelines. Through an empirical survey study covering 15 different SocIS platforms, we find that members do agree more and are more satisfied when guidelines have been developed by the community. These findings are important for platform providers to improve IQ and retain members, and also inform research on IQ in SocIS

Internal Crowdsourcing: Conceptual Framework, Structured Review, and Research Agenda

The use of IT-enabled crowdsourcing with employees in enterprises has increased substantially in recent years. This phenomenon, which we refer to as ‘internal crowdsourcing’, is distinct both from external crowdsourcing with end users and from hierarchy-based work with employees. A literature stream has emerged that corresponds with the increased relevance of internal crowdsourcing in practice. The purpose of this review paper of internal crowdsourcing is to provide conceptual development, synthesise the literature, and provide a research agenda. In the review reported in this paper, we systematically analysed and critically reviewed the literature in this domain published thus far (74 papers). We found useful findings and insights into a new and relevant IT-enabled phenomenon. At the same time, we also found conflicting definitions and conceptualisation, as well as research efforts that are not well integrated. The paper supports future research on internal crowdsourcing by providing improved conceptualisation, consolidating insights, and identifying important areas for future research

Decision Making in Emergency Management: The Role of Social Media

Researchers and practitioners alike recognise the importance of emergency management (EM) in limiting the adverse impacts of crisis events, as well as the promise of social media to support these efforts. Decision making, which is crucial to ensure the effective management of immediate, emerging, and sustained crises, is one facet of EM potentially affected by social media. While much research has investigated social media in a crisis context more generally, little is known thus far about what it means for EM decision making. In this paper, we investigate the current knowledge base of this phenomenon and infer from it factors that are crucial for its understanding. To this end, we propose an analytical framework of EM decision making based on previous work on complex problem solving and social media networks. We then systematically review and rethink existing research from a decision-centred point of view to identify and synthesise key findings that are relevant to the role of social media in the EM decision-making process. Finally, we outline the research gaps that need to be closed to arrive at a more comprehensive understanding of social media for EM decision support and to begin moving towards theoretically grounded explanations of the phenomenon

Ethical management of human-AI interaction : Theory development review

AI-based technologies have changed the nature of the symbiosis between humans and AI, and so strategic management of human-AI interaction in organizations requires deeper ethical considerations. Aligning AI with human values requires a systematic understanding of the ethical management of human-AI interaction. We conduct a theoretical review, from a sociotechnical perspective, and analyze ethical management of human-AI interaction through the lens of sociomateriality. Our systematic approach helps explain and clarify the interdependencies between two ethical perspectives – duty and virtue ethics – in sociotechnical systems. We also provide a theoretical framework that leads to seven avenues for future research