Abstract
As “big and broad” social media data continues to expand and become a more prevalent source for research, much remains to be understood about its epistemological and methodological implications. Drawing on an original data set of 12,732 research articles using social media data, we employ a novel dictionary-based approach to map the use of methods. Specifically, our approach draws on a combination of manual coding and embedding-enhanced query expansion. We cluster journals in groups of densely connected research communities to investigate how heterogeneous these groups are in terms of the
methods used. First, our results indicate that research in this domain is largely organized by methods. Some communities tend to have a monomethod culture, and others combine methods in novel ways. Comparing practices across communities, we observe that computational methods have penetrated many research areas but not the research space surrounding ethnography. Second, we identify two core axes of variation—social sciences vs. computer science and methodological individualism vs. relationalism—that organize the domain as a whole, suggesting new methodological divisions and debates.
methods used. First, our results indicate that research in this domain is largely organized by methods. Some communities tend to have a monomethod culture, and others combine methods in novel ways. Comparing practices across communities, we observe that computational methods have penetrated many research areas but not the research space surrounding ethnography. Second, we identify two core axes of variation—social sciences vs. computer science and methodological individualism vs. relationalism—that organize the domain as a whole, suggesting new methodological divisions and debates.
Originalsprog | Engelsk |
---|---|
Tidsskrift | Quantitative Science Studies |
Vol/bind | 4 |
Udgave nummer | 4 |
Sider (fra-til) | 976-996 |
ISSN | 2641-3337 |
DOI | |
Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:This research was supported by the DISTRACT Advanced Grant project, grant 834540 from the European Research Council (ERC).
Publisher Copyright:
© 2023 Yangliu Fan, Sune Lehmann, and Anders Blok.