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 structures can be found. Since some rumors are easier for individuals to verify than others, our results have implications for the priorities of journalists and official sources.

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 media communication of opinion leaders on Twitter with extended narrative analysis methodology finding different narratives that were mapped within the inhomogeneous anti-vaccination movements. The results show that both countries’ main narratives against vaccination are very similar, but the main difference stems from Brazil’s stronger politicization of vaccines.

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.

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 through multiple rounds of evaluation in the form of focus group discussions and questionnaires with ethics board members and SMA experts. The extended framework, encompassing a total of five iterative ethical reflection phases, provides simplified ethical guidance for SMA researchers and facilitates the ethical self-examination of research projects involving social media data.