1887
Volume 30, Issue 1
  • ISSN 1384-6655
  • E-ISSN: 1569-9811

Abstract

This article reviews Mapping texts: Computational text analysis for the social sciences

 

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2025-06-19
2025-07-19
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References

  1. Apache Software Foundation
    Apache Software Foundation. (n.d.). Apache OpenNLP 2.5.1 documentation. RetrievedDecember 20, 2024, fromhttps://opennlp.apache.org/docs/
    [Google Scholar]
  2. Crane, H.
    (2018) Probabilistic foundations of statistical network analysis. Chapman and Hall/CRC. 10.1201/9781315209661
    https://doi.org/10.1201/9781315209661 [Google Scholar]
  3. Cranmer, S. J., Desmarais, B. A., & Morgan, J. W.
    (2020) Inferential network analysis. Cambridge University Press. 10.1017/9781316662915
    https://doi.org/10.1017/9781316662915 [Google Scholar]
  4. Dicks, B., Flewitt, R., Lancaster, L., & Pahl, K.
    (2011) Multimodality and ethnography: Working at the intersection. Qualitative Research, 11(3), 227–237. 10.1177/1468794111400682
    https://doi.org/10.1177/1468794111400682 [Google Scholar]
  5. Egbert, J., Biber, D., & Gray, B.
    (2022) Designing and evaluating language corpora: A practical framework for corpus representativeness. Cambridge University Press. 10.1017/9781316584880
    https://doi.org/10.1017/9781316584880 [Google Scholar]
  6. Griswold, W.
    (1987) The fabrication of meaning: Literary interpretation in the United States, Great Britain, and the West Indies. American Journal of Sociology, 92(5), 1077–1117. 10.1086/228628
    https://doi.org/10.1086/228628 [Google Scholar]
  7. Heaps, H. S.
    (1978) Information retrieval: Computational and theoretical aspects. Academic Press, Inc.
    [Google Scholar]
  8. Herdan, G.
    (1960) Type-token mathematics: A textbook of mathematical linguistics. Mouton & Co.
    [Google Scholar]
  9. Kusner, M. J., Sun, Y., Kolkin, N. I., & Weinberger, K. Q.
    (2015) From word embeddings to document distances. InF. Bach & D. Blei (Eds.), ICML’15: Proceedings of the 32nd international conference on machine learning (Vol.371, pp.957–966). JMLR.org
    [Google Scholar]
  10. Lee, M., & Martin, J. L.
    (2015) Coding, counting and cultural cartography. American Journal of Cultural Sociology, 31, 1–33. 10.1057/ajcs.2014.13
    https://doi.org/10.1057/ajcs.2014.13 [Google Scholar]
  11. Livingstone, S. R., & Russo, F. A.
    (2018) The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English. PloS ONE, 13(5), Article e0196391. 10.1371/journal.pone.0196391
    https://doi.org/10.1371/journal.pone.0196391 [Google Scholar]
  12. Luo, H.
    (2023) Advances in multimodal learning: Pedagogies, technologies, and analytics. Frontiers in Psychology, 141, Article 1286092. 10.3389/978‑2‑8325‑3917‑0
    https://doi.org/10.3389/978-2-8325-3917-0 [Google Scholar]
  13. Minhas, S., Hoff, P. D., & Ward, M. D.
    (2019) Inferential approaches for network analysis: AMEN for latent factor models. Political Analysis, 27(2), 208–222. 10.1017/pan.2018.50
    https://doi.org/10.1017/pan.2018.50 [Google Scholar]
  14. Montani, I., Honnibal, M., Boyd, A., Van Landeghem, S., & Peters, H.
    (2023) explosion/spaCy (Version 3.7.2) [Computer software]. Zenodo. 10.5281/zenodo.10009823
    https://doi.org/10.5281/zenodo.10009823 [Google Scholar]
  15. R Core Team
    R Core Team (2023) R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
    [Google Scholar]
  16. Roberts, M. E., Stewart, B. M., & Tingley, D.
    (2019) Stm: An R package for structural topic models. Journal of Statistical Software, 91(2), 1–40. 10.18637/jss.v091.i02
    https://doi.org/10.18637/jss.v091.i02 [Google Scholar]
  17. Speed, J. G.
    (1893) Do newspapers now give the news?The Forum, 151, 705–711.
    [Google Scholar]
  18. Stoltz, D. S., & Taylor, M. A.
    (2019) Concept Mover’s Distance: Measuring concept engagement via word embeddings in texts. Journal of Computational Social Science, 21, 293–313. 10.1007/s42001‑019‑00048‑6
    https://doi.org/10.1007/s42001-019-00048-6 [Google Scholar]
  19. Taylor, M. A., & Stoltz, D. S.
    (2020) Integrating semantic directions with concept mover’s distance to measure binary concept engagement. Journal of Computational Social Science, 4(1), 231–242. 10.1007/s42001‑020‑00075‑8
    https://doi.org/10.1007/s42001-020-00075-8 [Google Scholar]
  20. Tufte, E. R.
    (1974) Data analysis for politics and policy. Prentice-Hall.
    [Google Scholar]
  21. Wijffels, J.
    (2023) Udpipe (Version 0.8.11) [R package]. https://CRAN.R-project.org/package=udpipe
    [Google Scholar]
  22. Zipf, G. K.
    (1949) Human behavior and the principle of least effort. Addison-Wesley Press.
    [Google Scholar]
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