The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Programmed method: developing a toolset for capturing and analyzing tweets
Abstract
Purpose: – 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. Design/methodology/approach: – 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. Findings: – 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. Practical implications: – 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. Originality/value: – 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.
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Cites
Reassembling the Social: An Introduction to Actor-Network-Theory
Latour, B. (2005) · doi:10.1093/oso/9780199256044.001.0001 · Cited by 16,778
Reassembling the social: An introduction to actor‐network‐theory
Turnbull, J. (2008) · New Zealand Geographer · doi:10.1111/j.1745-7939.2008.00151_4.x · Cited by 7,617
boyd, D., & Crawford, K. (2012) · Information, Communication & Society · doi:10.1080/1369118x.2012.678878 · Cited by 5,479
Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., et al. (2009) · Science · doi:10.1126/science.1167742 · Cited by 3,365
Winner, L. (2017) · Computer Ethics · doi:10.4324/9781315259697-21 · Cited by 2,317
(2013) · The MIT Press eBooks · doi:10.7551/mitpress/9302.001.0001 · Cited by 1,160
The Coming Crisis of Empirical Sociology
Savage, M., & Burrows, R. (2007) · Sociology · doi:10.1177/0038038507080443 · Cited by 914
Thrift, N. (2005) · doi:10.4135/9781446211458 · Cited by 890
Rogers, R. (2013) · The MIT Press eBooks · doi:10.7551/mitpress/8718.001.0001 · Cited by 746
Interactive dynamics for visual analysis
Heer, J., & Shneiderman, B. (2012) · Communications of the ACM · doi:10.1145/2133806.2133821 · Cited by 474
Cited by
Climate change on Twitter: Content, media ecology and information sharing behaviour
Veltri, G. A., & Atanasova, D. (2017) · Public Understanding of Science · doi:10.1177/0963662515613702 · Cited by 217
Keuchenius, A., Törnberg, P., & Uitermark, J. (2021) · PLOS ONE · doi:10.1371/journal.pone.0256696 · Cited by 27
Metadata
- Authors
- Borra, E., & Rieder, B.
- Venue
- Aslib Journal of Information Management
- Publisher
- Emerald
- Published
- 2014-05-19
- Volume
- 66
- Issue
- 3
- Pages
- 262-278
- ISSN
- 0001-253X (ISSN-L)
- 2050-3806
- OpenAlex
- W2047975424
- Cited by
- 262
- References
- 27
- FWCI
- 93.57
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.