The purpose of this paper is to introduce Digital Methods Initiative Twitter Capture and Analysis Toolset, a toolset for capturing and analyzing Twitter data. Instead of just presenting a technical paper detailing the system, however, the authors argue that the type of data used for, as well as the methods encoded in, computational systems have epistemological repercussions for research. The authors thus aim at situating the development of the toolset in relation to methodological debates in the social sciences and humanities.
The authors review the possibilities and limitations of existing approaches to capture and analyze Twitter data in order to address the various ways in which computational systems frame research. The authors then introduce the open-source toolset and put forward an approach that embraces methodological diversity and epistemological plurality.
The authors find that design decisions and more general methodological reasoning can and should go hand in hand when building tools for computational social science or digital humanities.
Besides methodological transparency, the software provides robust and reproducible data capture and analysis, and interlinks with existing analytical software. Epistemic plurality is emphasized by taking into account how Twitter structures information, by allowing for a number of different sampling techniques, by enabling a variety of analytical approaches or paradigms, and by facilitating work at the micro, meso, and macro levels.
The paper opens up critical debate by connecting tool design to fundamental interrogations of methodology and its repercussions for the production of knowledge. The design of the software is inspired by exchanges and debates with scholars from a variety of disciplines and the attempt to propose a flexible and extensible tool that accommodates a wide array of methodological approaches is directly motivated by the desire to keep computational work open for various epistemic sensibilities.
The authors would like to thank the special issue editors and the anonymous reviewers, as well as Noortje Marres, David Moats, Richard Rogers, Natalia Sanchez Querubin, Emma Uprichard, Lonneke van der Velden, and Esther Weltevrede for their useful comments, and Emile den Tex for his technical contributions. This project has benefited from a grant by the ESRC Digital Social Research Programme and the Centre for the Study of Invention and Social Process (Goldsmiths, University of London).
Borra, E. and Rieder, B. (2014), "Programmed method: developing a toolset for capturing and analyzing tweets", Aslib Journal of Information Management, Vol. 66 No. 3, pp. 262-278. https://doi.org/10.1108/AJIM-09-2013-0094Download as .RIS
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