\u3ci\u3eSnowedOut Atlanta\u3c/i\u3e: Examining digital emergence on facebook during a crisis

Individuals in emergencies form spontaneous, emergent groups to respond and recover. With the rise of social media use in crises, academics and professionals must be aware of how groups digitally coordinate emergent response efforts. This paper examines digital emergence through the case of SnowedOut Atlanta, a Facebook group formed during the 2014 ice storms in Atlanta. The posts and actions of the group members are in line with those of traditional emergent groups. For example, group members shared informational, material, and emotional support. The findings also provide implications for practitioners and insight into the communication of such groups. In particular, emergency managers have an opportunity to seek out and partner with these types of groups in future similar events

Coming Together Around Hashtags: Exploring the Formation of Digital Emergent Citizen Groups

It has been well established that during and after crisis or emergency events, groups of citizens come together to help one another, solve problems, and manage recovery or cleanup. These groups are called emergent citizen groups. They form organically and often disband when the emergency is managed. This study proposes that similar types of groups now form in digital spaces during and after crises. The authors studied conversation on Twitter that used the hashtag “#PrayforUSC” after the murder-suicide that took place at the University of South Carolina in 2015. Initial results indicate that hashtags can function as focal points or catalysts for digital emergent citizen groups. More research should be done to determine whether and how these groups form, function, and disperse

Social Media, Parades and Protest

No abstract available

Rethinking populist discourse from Latin America

The aim of this article is to explore some of the ideological and empirical limits of studies on populism from a perspective based on Latin American history and theories, on one hand, and current ideas about digitalization and political discourse, on the other. I will first argue that studies on populism have a monolingual bias that conceals an ethnocentric view on academic research. As a consequence, when the term “populism” is applied to Latin American political discourse and history, it implies a pejorative view on democracies other than liberal European. Leaving aside this perspective, I will then present a different view of Latin American populisms, which allows for a richer, more complex perspective, including the key role of “the people” as a discursive actor that can even dispense with a populist leader, especially in the case of mediatized democracies. As a case study, I will analyze activism in Chile by observing Twitter’s Trending Topics (TT) during the first week of the mass protests in October 2019. The analysis of TT hashtags helped us to better desccribe this process as one of handcrafted algorithmic activism which developed at least four tactics: the formulation of explicit demands, off-hours tweetstorms, syntagmatic variation, and HT confrontation and appropriation

Enhancing Geospatial Data: Collecting and Visualising User-Generated Content Through Custom Toolkits and Cloud Computing Workflows

Through this thesis we set the hypothesis that, via the creation of a set of custom toolkits, using cloud computing, online user-generated content, can be extracted from emerging large-scale data sets, allowing the collection, analysis and visualisation of geospatial data by social scientists. By the use of a custom-built suite of software, known as the ‘BigDataToolkit’, we examine the need and use of cloud computing and custom workflows to open up access to existing online data as well as setting up processes to enable the collection of new data. We examine the use of the toolkit to collect large amounts of data from various online sources, such as Social Media Application Programming Interfaces (APIs) and data stores, to visualise the data collected in real-time. Through the execution of these workflows, this thesis presents an implementation of a smart collector framework to automate the collection process to significantly increase the amount of data that can be obtained from the standard API endpoints. By the use of these interconnected methods and distributed collection workflows, the final system is able to collect and visualise a larger amount of data in real time than single system data collection processes used within traditional social media analysis. Aimed at allowing researchers without a core understanding of the intricacies of computer science, this thesis provides a methodology to open up new data sources to not only academics but also wider participants, allowing the collection of user-generated geographic and textual content, en masse. A series of case studies are provided, covering applications from the single researcher collecting data through to collection via the use of televised media. These are examined in terms of the tools created and the opportunities opened, allowing real-time analysis of data, collected via the use of the developed toolkit