Integrating human and machine coding to measure political issues in ethnic newspaper articles

Abstract

The voices of racial minority groups have rarely been examined systematically with large-scale text analysis in political science. This study fills such a gap by applying an integrated classification framework to the analysis of the commonalities and differences in political issues that appeared in 78,305 articles from Asian American and African American newspapers from the 1960s to the 1980s. The automated text classification shows that Asian American newspapers focused on promoting collective gains more often than African American newspapers. Conversely, African American newspapers concentrated on preventing collective losses more than Asian American newspapers. The content analysis demonstrates that the issue priorities varied between the corpora, especially with respect to policy contexts. Gaining access to government resources was a more urgent issue for Asian Americans, while reducing or ending state violence, such as police brutality, was a more pressing matter for African Americans. It also helped avoid extreme interpretations of the machine coding, as the misalignment of political agendas between the two corpora widened up to 10 times when the training data were measured using the minimum, rather than the maximum, reliability threshold.

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Data availability

Not available due to copyright restrictions.

Code availability

All replication files can be found at https://github.com/jaeyk/content-analysis-for-evaluating-ML-performances.

Notes

  1. 1.

    For more information, see https://www.icpsr.umich.edu/icpsrweb/ICPSR/series/163.

  2. 2.

    For more information, see https://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/6841.

  3. 3.

    For more information, see https://www.pewresearch.org/topics/national-survey-of-latinos/.

  4. 4.

    For more information, see https://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/3832.

  5. 5.

    For more information, see https://naasurvey.com/data/.

  6. 6.

    For more information, see https://cmpsurvey.org/.

  7. 7.

    For more information, see https://www.proquest.com/products-services/ethnic_newswatch.html.

  8. 8.

    Greaves, Kay, “Davis Bail is Canceled; Poindexter Out on Bail,” Oakland Post, October 22, 1970: 13.

  9. 9.

    Chin, Karen, ”Pacific/Asian Elderly Conference: Social Service Providers Must Get Their ’Act Together’,” International Examiner, April 30, 1979.

  10. 10.

    Fleming, Thomas,“Thomas Fleming’s Weekly Report,” Sun Reporter, August 2, 1975:7

  11. 11.

    Berling, Lynn, “‘Post’ Tries to be Only Daily for Black Community’,’ Oakland Post, February 15, 1981: 6.

  12. 12.

    For more information, see https://www.proquest.com/products-services/ethnic_newswatch.html.

  13. 13.

    Several studies have demonstrated how this measure tends to overestimate the true agreement among human coders [8, 69, 102].

  14. 14.

    In practice, a kappa smaller than or equal to 0 indicates no agreement, a kappa in the 0.01–0.02 range indicates slight agreement, a kappa in the 0.21–0.40 range indicates fair agreement, a kappa in the 0.41–0.60 range indicates moderate agreement, a kappa in the 0.61–0.80 range indicates substantial agreement, and a kappa in the 0.81–1 range indicates an almost perfect agreement ([76], 279).

  15. 15.

    I only used the top 5000 most frequently appearing terms because Zipf’s law expects frequently appearing features in documents to be a small fraction [118, 119]. The rest of the features will only increase sparsity in the training data and slow down the algorithmic process.

  16. 16.

    Anonymous, “Cairo, Illinois: From Exploitation To Freedom,” Sun Reporter, March 27, 1971: 8.

  17. 17.

    Iwamoto, Gary, “A Picture of the 70’s,” International Examiner, December 31, 1979: 8.

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Kim, J.Y. Integrating human and machine coding to measure political issues in ethnic newspaper articles. J Comput Soc Sc (2021). https://doi.org/10.1007/s42001-020-00097-2

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Keywords

  • Computational text analysis
  • Asian American politics
  • African American politics
  • Ethnic newspapers
  • Coalition building
  • Community organizing