No abstract

Social movements scholarship on the role of coalitions in advancing social change claims that communication across ideological boundaries can foster a collective identity among diverse groups of activists. New communications technology, especially activists' widespread adoption of social media, calls into question whether these claims apply equally to online social media-based coalitions. Using the case of the Egyptian revolution in the Arab Spring, we conduct a series of social network analyses of the Twitter networks of activists. We find that social movements coalitions theory accurately predicts the conditions under which coalitions form and dissolve for online activists, as it does for on-the-ground activists. Among activists of diverse ideologies, we identify a pattern of solidarity in the early days of the revolutionary period, followed by a period of schism after a military crackdown on protestors. This research extends social movements theory to the sphere of digital activism.

As social media become a staple for knowledge discovery and sharing, questions arise about how self-organizing communities manage learning outside the domain of organized, authority-led institutions. Yet examination of such communities is challenged by the quantity of posts and variety of media now used for learning. This paper addresses the challenges of identifying (1) what information, communication, and discursive practices support successful online communities, (2) whether such practices are similar on Twitter and Reddit, and (3) whether machine learning classifiers can be successfully used to analyze larger datasets of learning exchanges. This paper builds on earlier work that used manual coding of learning and exchange in Reddit ‘Ask’ communities to derive a coding schema we refer to as ‘learning in the wild’. This schema of eight categories: explanation with disagreement, agreement, or neutral presentation; socializing with negative, or positive intent; information seeking; providing resources; and comments about forum rules and norms. To compare across media, results from coding Reddit’s AskHistorians are compared to results from coding a sample of #Twitterstorians tweets (n = 594). High agreement between coders affirmed the applicability of the coding schema to this different medium. LIWC lexicon-based text analysis was used to build machine learning classifiers and apply these to code a larger dataset of tweets (n = 69,101). This research shows that the ‘learning in the wild’ coding schema holds across at least two different platforms, and is partially scalable to study larger online learning communities.

This article examines the role of Facebook and YouTube in potentially exposing people to COVID-19 vaccine–related misinformation. Specifically, to study the potential level of exposure, the article models a uni-directional information-sharing pathway beginning when a Facebook user encounters a vaccine-related post with a YouTube video, follows this video to YouTube, and then sees a list of related videos automatically recommended by YouTube. The results demonstrate that despite the efforts by Facebook and YouTube, COVID-19 vaccine–related misinformation in the form of anti-vaccine videos propagates on both platforms. Because of these apparent gaps in platform-led initiatives to combat misinformation, public health agencies must be proactive in creating vaccine promotion campaigns that are highly visible on social media to overtake anti-vaccine videos’ prominence in the network. By examining related videos that a user potentially encounters, the article also contributes practical insights to identify influential YouTube channels for public health agencies to collaborate with on their public service announcements about the importance of vaccination programs and vaccine safety.

On May 25, 2018, the European Union (EU) implemented the General Data Protection Regulation (GDPR) to protect individuals' privacy and data. This regulation has far-reaching implications as it applies to any organization that deals with data of EU residents. By studying the discussion about this regulation on Twitter, our goal is to examine public opinions and organizational public relations (PR) strategies about GDPR. The results show that the regulation is being actively discussed by a variety of stakeholders, but especially by cybersecurity and IT-related firms and consultants. At the same time, some of the stakeholders that were expected to have a more active role were less involved, including companies that store or process personal data, government and regulatory bodies, mainstream media, and academics. The results also show that the stakeholders mostly have one-way rather than two-way communication with their audiences, thus fulfilling the rhetorical than relational function of PR.