The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of U.S. government arts funding
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Cites
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Griffiths, T. L., & Steyvers, M. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307752101 · Cited by 6,049
Blei, D. M. (2012) · Communications of the ACM · doi:10.1145/2133806.2133826 · Cited by 5,516
Self-citationText as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts
Grimmer, J., & Stewart, B. M. (2013) · Political Analysis · doi:10.1093/pan/mps028 · Cited by 3,297 · cited 4×
“Like any clustering technique, the method should be employed as a heuristic tool in combination with additional information by a research team that includes subject-area experts (Grimmer and Stewart, 2011).”
BackgroundMethodInfluentialHow to analyze political attention with minimal assumptions and costs
Quinn, K. M., Monroe, B. L., Colaresi, M., Crespin, M. H., & Radev, D. R. (2010) · American Journal of Political Science · doi:10.1111/j.1540-5907.2009.00427.x · Cited by 671
Cited by
Can Large Language Models Transform Computational Social Science?
Ziems, C., Held, W., Shaikh, O., Chen, J., Zhang, Z., & Yang, D. (2023) · arXiv · doi:10.48550/arxiv.2305.03514 · Cited by 839
Can Large Language Models Transform Computational Social Science?
Ziems, C., Held, W., Shaikh, O., Chen, J., Zhang, Z., & Yang, D. (2024) · Computational Linguistics · doi:10.1162/coli_a_00502 · Cited by 585
The Geometry of Culture: Analyzing the Meanings of Class through Word Embeddings
Kozlowski, A. C., Taddy, M., & Evans, J. A. (2019) · American Sociological Review · doi:10.1177/0003122419877135 · Cited by 499
Schmiedel, T., Müller, O., & vom Brocke, J. (2019) · Organizational Research Methods · doi:10.1177/1094428118773858 · Cited by 319
Machine Learning for Sociology
Molina, M., & Garip, F. (2019) · Annual Review of Sociology · doi:10.1146/annurev-soc-073117-041106 · Cited by 295
Metadata
- Authors
- DiMaggio, P., Nag, M., & Blei, D.
- Venue
- Poetics
- Publisher
- Elsevier BV
- Published
- 2013-12
- Volume
- 41
- Issue
- 6
- Pages
- 570-606
- ISSN
- 0304-422X (ISSN-L)
- OpenAlex
- W2117667023
- Cited by
- 1,145
- References
- 5
- FWCI
- 126.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of U.S. government arts funding. https://app.cochat.ai/papers/10.1016/j.poetic.2013.08.004
- The paper
- DiMaggio, P., Nag, M., & Blei, D. (2013). Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of U.S. government arts funding. Poetics. https://doi.org/10.1016/j.poetic.2013.08.004
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
