Crossroads in Cultural Studies Conference 14-17th December 2016 Program Index

6H
Towards Thick Data: Stories from the Field (Chair, Liam Magee)
Heather Ford*, Walid Al-Saqaf, Tanja Bosch & Lone Sorensen
Geertz’s Map
We chart the histories of the term “thick data” (Wang 2014) to its roots in Geertz”s (1973) writing on “thick
description”, outlining the practical implications for Geertz”s theory of culture to the study of online
behavior. Geertz writes that “culture is not a power, something to which social events, behaviors,
institutions, or processes can be causally attributed; it is a context, something within which they can be
intelligibly – that is, thickly – described”. While the majority of tools or instruments for studying “big” social
media data enable us to observe patterns of behavior, we need theoretical frameworks to interpret that
behavior. Theory makes thick description possible, writes Geertz, not by the analyst generalizing across cases
but by generalizing within them. We applied this principle to the study of political conflict and the case of
Twitter discussions of the 2015/6 South African State of the Nation Address. Bespoke quantitative tools
provided an observational lens, and framing theory (Entman 1993) enabled us to develop qualitative
interpretations. This two-step approach is necessary to move towards interpretations of behavior in context
and, while quantitative tools that enable observation are clearly important, interpretation requires the use
of relevant theory.
Luigi Di Martino Qualitative analysis within computational Twitter Analysis
Large social media datasets paradoxically are both qualitative and quantitative, since they contain
quantifiable information, such as number of followers, retweets, mentions, but also texts and images that
require a qualitative approach. However, the support of machines is unavoidable for the analysis of large
datasets, due to the huge amount of information that would otherwise require a long time to be manually
processed and classified. Indeed, digital maps enable one to zoom in and out in order to observe data at
different scales, computational analysis of social media data offers multiple lenses for analysing patterns in
behaviour. Beyond metrics and network visualisations, analysing images and memes qualitatively according
to the author’s tone and triangulating observational findings to avoid misleading interpretation of data
enable further analysis. By analysing the Twitter data collected during the G20-2014 in Brisbane, this paper
will illustrate a mixed methodological approach for the study of Public Diplomacy on Twitter. It will suggest
the necessity of combining both quantitative and qualitative methodological strategies to comprehend
context and cross-platform flow of information. Drawing on research findings, we offer two accounts of data
as it emerged from our project: as thin data where prevalence is given to digital content, data visualisations
and the media “message”; and thick data where the politics of the digital are enmeshed in socio-cultural
mediations and conceptions. This is not a dichotomy, but a complex interweaving of practice and perception
that is gendered, “unthought” and reflexive; individual and institutional: part of the complexity and
embeddedness of data in our everyday. It is this that needs critical attention if we are to understand the
politics of data and its” impact across cultures, subcultures and institutions for the future.
Helen Thornham* & Sarah Maltby
Thick data and the military
Data, big data and datalogical systems are already “an established presence in our everyday cultural lives”
(Beer, 2015:2) and this means that the material and embodied configurations of data are both normative
and novel. For the MoD (British Ministry of Defence, stakeholder of our ESRC research project), big data and
social media go hand in hand – generating incredible opportunity and risk that feed into a growing schism
between how organisations use and constitute data on the one hand, and how data is generated and
conceptualised through everyday digital mediations on the other. Drawing on research findings, we offer
two accounts of data as it emerged from our project: as thin data where prevalence is given to digital
156