This chapter develops an account of epistemic nihilism—roughly, the rejection of truth’s intrinsic or instrumental value in favor of statements that reject or obscure truth to secure an advantage for the speaker—by examining three instances of such nihilism: lying, bullshit, and trolling. It further argues that epistemic nihilism, exacerbated by changes in the media landscape, can pose a significant threat to liberal democratic institutions and ideals by undermining the democratic ideal of good faith engagement on a level playing field, while (...) also encouraging undemocratic actions (e.g., terrorism) among interlocutors who take the nihilist’s claims seriously. Finally, this chapter argues that in extreme cases, we are justified in denying epistemic nihilists a platform from which to speak by drawing a parallel with vexatious litigant laws that deny individuals the right to petition courts for redress on the grounds that abuse of that right results in significant harm to both individuals and the legal system itself. (shrink)

This article explores the relationship between deliberative democracy, the Internet, and systems theory’s thoughts on diversity. After introducing Habermas’s theory of deliberative democracy and how diversity fits into it, the article discusses various ideas about whether and how it could work on the Internet. Next, the article looks at research into diversity done in the field of complex adaptive systems, showing that diversity has both good and bad effects, but is clearly preferred for the purpose of survival. The article concludes (...) with an analysis of how the results of systems theory’s study of diversity can assist society in bringing democracy to the Web. (shrink)

Social media posts are full of potential for data mining and analysis. Recognizing this potential, platform providers increasingly restrict free access to such data. This shift provides new challenges for social scientists and other non-profit researchers who seek to analyze public posts with a purpose of better understanding human interaction and improving the human condition. This paper seeks to outline some of the recent changes in social media data analysis, with a focus on Twitter, specifically. Using Twitter data from a (...) 24-hour period following The Sisters in Spirit Candlelight Vigil, sponsored by the Native Women’s Association of Canada, this article compares three free-use Twitter application programming interfaces for capturing tweets and enabling analysis. Although recent Twitter data restrictions limit free access to tweets, there are many dynamic options for social scientists to choose from in the capture and analysis of Twitter and other social media platform data. This paper calls for critical social media data analytics combined with traditional, qualitative methods to address the developing ‘data gold rush.’. (shrink)

The paper presents my first findings and reflections on how ordinary people may opportunistically and unpredictably respond to Internet censorship and tracking. I try to capture this process with the concept of ‘hacking multitude'. Working on a case study of the Turkish government's block of the social media platform Twitter, I argue that during systemic data choke-points, a multitude of users might acquire a certain degree of reflexivity over ubiquitous software of advanced techno-capitalism. Resisting naïve parallels between urban streets and (...) virtual global streets, the article draws on Fuller's ‘media ecologies' to make sense of complex and dynamic interactions between processes and materialities, strategies of communication and mundane practices. Such a dense space is mostly invisible to network and traffic analysis, although it comes alive under the magnifying lens of digital ethnography. As the Turkish government tried to stop protesters on both the urban and the Twitter spheres, alternative material configurations and new hybrid formations and practices emerged. I try to bring this process alive following the traces – that is, a combination of digital data and materialities – of a social space between the protest for Twitter access, the ‘digital coup' and the interactions that this situation determined. In the final section, I briefly explore two research trajectories which can further develop my initial formulation of a ‘hacking multitude'. I argue that a generalisation of hacking/multitude is problematic for the political, cultural or economic processes more directly associated with Big Data. (shrink)

Though full of promise, Big Data research success is often contingent on access to the newest, most advanced, and often expensive hardware systems and the expertise needed to build and implement such systems. As a result, the accessibility of the growing number of Big Data-capable technology solutions has often been the preserve of business analytics. Pay as you store/process services like Amazon Web Services have opened up possibilities for smaller scale Big Data projects. There is high demand for this type (...) of research in the digital humanities and digital sociology, for example. However, scholars are increasingly finding themselves at a disadvantage as available data sets of interest continue to grow in size and complexity. Without a large amount of funding or the ability to form interdisciplinary partnerships, only a select few find themselves in the position to successfully engage Big Data. This article identifies several notable and popular Big Data technologies typically implemented using large and extremely powerful cloud-based systems and investigates the feasibility and utility of development of Big Data analytics systems implemented using low-cost commodity hardware in basic and easily maintainable configurations for use within academic social research. Through our investigation and experimental case study, we found that not only are solutions like Cloudera’s Hadoop feasible, but that they can also enable robust, deep, and fruitful research outcomes in a variety of use-case scenarios across the disciplines. (shrink)

In the few years since the advent of ‘Big Data’ research, social media analytics has begun to accumulate studies drawing on social media as a resource and tool for research work. Yet, there has been relatively little attention paid to the development of methodologies for handling this kind of data. The few works that exist in this area often reflect upon the implications of ‘grand’ social science methodological concepts for new social media research. By contrast, we advance an abductively oriented (...) methodological suite designed to explore the construction of phenomena played out through social media. To do this, we use a software tool – Chorus – to illustrate a visual analytic approach to data. Informed by visual analytic principles, we posit a two-by-two methodological model of social media analytics, combining two data collection strategies with two analytic modes. We go on to demonstrate each of these four approaches ‘in action’, to help clarify how and why they might be used to address various research questions. (shrink)

Although the rapid growth of digital data and computationally advanced methods in the social sciences has in many ways exacerbated tensions between the so-called ‘quantitative’ and ‘qualitative’ approaches, it has also been provocatively argued that the ubiquity of digital data, particularly online data, finally allows for the reconciliation of these two opposing research traditions. Indeed, a growing number of ‘qualitatively’ inclined researchers are beginning to use computational techniques in more critical, reflexive and hermeneutic ways. However, many of these claims for (...) ‘quali-quantitative’ methods hinge on a single technique: the network graph. Networks are relational, allow for the questioning of rigid categories and zooming from individual cases to patterns at the aggregate. While not refuting the use of networks in these studies, this paper argues that there must be other ways of doing quali-quantitative methods. We first consider a phenomenon which falls between quantitative and qualitative traditions but remains elusive to network graphs: the spread of information on Twitter. Through a case study of debates about nuclear power on Twitter, we develop a novel data visualisation called the modulation sequencer which depicts the spread of URLs over time and retains many of the key features of networks identified above. Finally, we reflect on the role of such tools for the project of quali-quantitative methods. (shrink)