Anna-Katharina Jung

Since February 2020, the world has been facing a global pandemic of the SARS-CoV2 virus. All over the world, people have been urged to take protective measures. It is hoped that the implementation of widespread vaccination campaigns will defeat the pandemic in the long term. While many people are eager to be vaccinated against Covid-19, other voices in the population are highly critical of vaccination and protective measures, circulating much misinformation on social media. The movements opposing pandemic response measures are heterogeneous, including right-wing groups, spiritualists who deny science, citizens with existential fears, and those who equate vaccination with a loss of individual freedom. This study aims to map and compare the social media communication of anti-vaccination movements that defy social cohesion and circulate online misinformation in Germany and Brazil. By following a grounded theory approach suggested by Webb and Mallon (2007), we coded content from social ...

Clickbait to make people click on a linked article is commonly used on social media. We analyze the impact of clickbait on user interaction on Facebook in the form of liking, sharing and commenting. For this, we use a data set of more than 4,400 Facebook posts from 10 different news sources to analyze how clickbait in post headlines and in post text influences user engagement. The results of our study revealed that certain features (e.g., unusual punctuation and common clickbait phrases) increase user interaction, whereas others decrease engagement with Facebook posts. We further use our results to discuss the potential role of digital nudging in the context of clickbait. Our results contribute to understanding and making use of the effect of different framings in social media.

Warning messages are being discussed as a possible mechanism to contain the circulation of false information on social media. Their effectiveness for this purpose, however, is unclear. This article describes a survey experiment carried out to test two de

En route to the unravelling of today’s multiplicity of societal challenges, making sense of social data has become a crucial endeavour in Information Systems (IS) research. In this context, Social Media Analytics (SMA) has evolved to a promising field of data-driven approaches, guiding researchers in the process of collecting, analysing, and visualising social media data. However, the handling of such sensitive data requires careful ethical considerations to protect data subjects, online communities, and researchers. Hitherto, the field lacks consensus on how to safeguard ethical conduct throughout the research process. To address this shortcoming, this study proposes an extended version of a SMA framework by incorporating ethical reflection phases as an addition to methodical steps. Following a design science approach, existing ethics guidelines and expert interviews with SMA researchers and ethicists serve as the basis for redesigning the framework. It was eventually assessed thro...

So-called 'social bots' have garnered a lot of attention lately. Previous research showed that they attempted to influence political events such as the Brexit referendum and the US presidential elections. It remains, however, somewhat unclear what exactly can be understood by the term 'social bot'. This paper addresses the need to better understand the intentions of bots on social media and to develop a shared understanding of how 'social' bots differ from other types of bots. We thus describe a systematic review of publications that researched bot accounts on social media. Based on the results of this literature review, we propose a scheme for categorising bot accounts on social media sites. Our scheme groups bot accounts by two dimensions - Imitation of human behaviour and Intent.

Like many other industries, the media industry has been profoundly affected by social media. The public discuss the news on services such as Twitter, and some celebrity tweets are picked up by journalists and become news stories themselves. Information systems research into information diffusion has largely neglected these cross-platform diffusion patterns. To address this gap, the presented research in progress examines indicators of information spill-over between Twitter and ten German news websites, by detecting references in the form of URLs and mentions on both sides. Furthermore, the paper presents automatic and manual methods to identify two categories of spill-over, reference spill-over and content spill-over. Preliminary findings reveal differences between news outlets in how frequently they are referenced by Twitter users, and in how often they reference Twitter in their own stories.

Live streaming services like Facebook Live or Periscope allow their users to broadcast whatever and whenever they want on social media. This recently developed type of real-time broadcasting evokes a number of ethical concerns ranging from privacy, surveillance to intellectual property issues. Yet, despite its growing importance in contemporary society, there has been limited research on the ethical dimensions of live streaming. To close this gap, this study seeks to address the research question: What ethical aspects have to be considered for live streaming? To be able to derive holistic ethical norms, which are not limited to specific agents or contexts, this paper presents the design for an Online Delphi study with international experts from seven different fields: ethics, politics, law, journalism, software engineering, platform operators and users. The exploratory stage of the Delphi study has been conducted, including the development of the questionnaire and the recruitment of...

As false information may spread rapidly on social media, a profound understanding of how it can be debunked is required. This study offers empirical insights into the development of rumors after they are debunked, the various user groups who are involved in the process, and their network structures. As crisis situations are highly sensitive to the spread of rumors, Twitter posts from during the 2017 G20 summit are examined. Tweets regarding five rumors that were debunked during this event were manually coded into the following categories: rumor, debunking message, uncertainty about rumor, uncertainty about debunking message, and others. Our findings show that rumors which are debunked early and vehemently by official sources are the most likely to be stopped. When individuals participate in the process, they typically do so by sharing uncommented media content, as opposed to contributing user-generated content. Depending on the conditions in which a rumor arises, different network s...