References
- Bailey, M. A., Strezhnev, A., & Voeten, E. (2017). Estimating dynamic state preferences from United Nations voting data. Journal of Conflict Resolution, 61(2), 430–456. https://doi.org/10.1177/0022002715595700
- Barnes, T. D., & Beaulieu, E. (2017). Engaging women: Addressing the gender gap in women’s networking and productivity. PS: Political Science & Politics, 50(2), 461–466. https://doi.org/10.1017/S1049096516003000
- Beal, D. J., Cohen, R. R., Burke, M. J., & McLendon, C. L. (2003). Cohesion and performance in groups: A meta-analytic clarification of construct relations. Journal of Applied Psychology, 88(6), 989. https://doi.org/10.1037/0021-9010.88.6.989
- Becker, M. (2019). Importing the laboratory model to the social sciences: Prospects for improving mentoring of undergraduate researchers. Journal of Political Science Education, 1–13. https://doi.org/10.1080/15512169.2018.1505523
- Becker, M. (2020). Research for all: Creating opportunities for undergraduate research experiences across the curriculum. Taylor & Francis. https://doi.org/10.33774/apsa-2020-30zr5
- Bhandari, M., Einhorn, T. A., Swiontkowski, M. F., & Heckman, J. D. (2003). Who did what?: (Mis)perceptions about authors’ contributions to scientific articles based on order of authorship. JBJS, 85(8), 1605. https://doi.org/10.2106/00004623-200308000-00024
- Biagioli, M. (2016). Watch out for cheats in citation game. Nature News, 535(7611), 201. https://doi.org/10.1038/535201a
- Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3(Jan), 993–1022. http://www.jmlr.org/papers/v3/blei03a
- Brennan, P. M., Jubb, A., Baillie, J. K., & Partridge, R. W. (2013). Deciding authorship order. BMJ, 347, f7182. https://doi.org/10.1136/bmj.f7182
- Breuning, M., & Sanders, K. (2007). Gender and journal authorship in eight prestigious political science journals. PS: Political Science & Politics, 40(2), 347–351. https://doi.org/10.1017/S1049096507070564
- Chenoweth, E., & Belgioioso, M. (2019). The physics of dissent and the effects of movement momentum. Nature Human Behaviour, 3(10), 1088–1095. https://doi.org/10.1038/s41562-019-0665-8
- Dietrich, B. J., & Juelich, C. L. (2018). When presidential candidates voice party issues, does Twitter listen? Journal of Elections, Public Opinion and Parties, 28(2), 208–224. https://doi.org/10.1080/17457289.2018.1441847
- Fréchet, N., Savoie, J., & Dufresne, Y. (2019). Analysis of text-analysis syllabi: Building a text-analysis syllabus using scaling. PS: Political Science & Politics, 53(2), 338–343. https://doi.org/10.1017/S1049096519001732
- Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21(3), 267–297. https://doi.org/10.1093/pan/mps028
- Guberman, J., Shapiro, B., & Torchia, M. (2006). Making the right moves: A practical guide to scientific management for postdocs and new faculty. Howard Hughes Medical Institute and Burroughs Wellcome Fund.
- Halliday, M. A. K., & Hasan, R. (1976). Cohesion in English. Longman.
- Head, M. L., Holman, L., Lanfear, R., Kahn, A. T., & Jennions, M. D. (2015). The extent and consequences of p-hacking in science. PLoS Biology, 13(3), e1002106. https://doi.org/10.1371/journal.pbio.1002106
- Hosseini, P., Diab, M., & Broniatowski, D. A. (2019). Does causal coherence predict online spread of social media? In R. Thomson, H. Bisgin, C. Dancy, & A. Hyder (Eds.), Social, cultural, and behavioral modeling (pp. 184–193). Springer International Publishing.
- Huckfeldt, R., Beck, P. A., Dalton, R. J., & Levine, J. (1995). Political environments, cohesive social groups, and the communication of public opinion. American Journal of Political Science, 39(4), 1025. https://doi.org/10.2307/2111668
- Kaakinen, J. K., Salonen, J., Venäläinen, P., & Hyönä, J. (2011). Influence of text cohesion on the persuasive power of expository text. Scandinavian Journal of Psychology, 52(3), 201–208. https://doi.org/10.1111/j.1467-9450.2010.00863.x
- Kadera, K. (2013). The social underpinnings of women’s worth in the study of world politics: Culture, leader, emergence, and coauthorship. International Studies Perspectives, 14(4), 463–475. https://doi.org/10.1111/insp.12028
- King, G., Pan, J., & Roberts, M. E. (2014). Reverse-engineering censorship in China: Randomized experimentation and participant observation. Science, 345(6199), 1251722. https://doi.org/10.1126/science.1251722
- Kirke, C. (2010). Military cohesion, culture and social psychology. Defence & Security Analysis, 26(2), 143–159. https://doi.org/10.1080/14751798.2010.488856
- Kiser, G. L. (2018). No more first authors, no more last authors. Nature, 561(7724), 435–436. https://doi.org/10.1038/d41586-018-06779-2
- Klebanov, B. B., Diermeier, D., & Beigman, E. (2008). Lexical cohesion analysis of political speech. Political Analysis, 16(4), 447–463. https://doi.org/10.1093/pan/mpn007
- Lehrke, J. P. (2013). A cohesion model to assess military arbitration of revolutions. Armed Forces & Society, 40(1), 146–167. https://doi.org/10.1177/0095327X12459851
- Levitsky, S. R., & Way, L. A. (2012). Beyond patronage: Violent struggle, ruling party cohesion, and authoritarian durability. Perspectives on Politics, 10(4), 869–889. https://doi.org/10.1017/S1537592712002861
- Liu, A. H., Shair-Rosenfield, S., Vance, L. R., & Csata, Z. (2018). Linguistic origins of gender equality and women’s rights. Gender & Society, 32(1), 82–108. https://doi.org/10.1177/0891243217741428
- Loken, E., & Gelman, A. (2017). Measurement error and the replication crisis. Science, 355(6325), 584–585. https://doi.org/10.1126/science.aal3618
- McManus, R. W. (2017). The impact of context on the ability of leaders to signal resolve. International Interactions, 43(3), 453–479. https://doi.org/10.1080/03050629.2016.1171764
- Mcmurtrie, B. (2016, March 13). The promise and peril of cluster hiring. The Chronicle of Higher Education. https://www.chronicle.com/article/The-PromisePeril-of/235679
- McNamara, D. S., Graesser, A. C., McCarthy, P. M., & Cai, Z. (2014). Automated evaluation of text and discourse with Coh-Metrix. Cambridge University Press.
- McNutt, M. K., Bradford, M., Drazen, J. M., Hanson, B., Howard, B., Jamieson, K. H., Kiermer, V., Marcus, E., Pope, B. K., Schekman, R., Swaminathan, S., Stang, P. J., & Verma, I. M. (2018). Transparency in authors’ contributions and responsibilities to promote integrity in scientific publication. Proceedings of the National Academy of Sciences, 115(11), 2557–2560. https://doi.org/10.1073/pnas.1715374115
- Mimno, D., Wallach, H. M., Talley, E., Leenders, M., & McCallum, A. (2011). Optimizing semantic coherence in topic models. Proceedings of the Conference on Empirical Methods in Natural Language Processing (pp. 262–272). Association for Computational Linguistics, Chicago. https://dl.acm.org/doi/10.5555/2145432.2145462
- Morris, J., & Hirst, G. (1991). Lexical cohesion computed by thesaural relations as an indicator of the structure of text. Computational Linguistics, 17(1), 21–48. https://dl.acm.org/doi/10.5555/971738.971740
- Nelson, L. K. (2017). Computational grounded theory: A methodological framework. Sociological Methods & Research, 49(1), 3–42. https://doi.org/10.1177/0049124117729703
- Niederhoffer, K. G., & Pennebaker, J. W. (2002). Linguistic style matching in social interaction. Journal of Language and Social Psychology, 21(4), 337–360. https://doi.org/10.1177/026192702237953
- Peterson, A., & Spirling, A. (2018). Classification accuracy as a substantive quantity of interest: Measuring polarization in westminster systems. Political Analysis, 26(1), 120–128. https://doi.org/10.1017/pan.2017.39
- West, J. D., Jacquet, J., King, M. M., Correll, S. J., & Bergstrom, C. T. (2013). The role of gender in scholarly authorship. Plos One, 8(7), e66212. https://doi.org/10.1371/journal.pone.0066212
- Windsor, L. (2020). The language of radicalization: Female Internet recruitment to participation in ISIS activities. Terrorism and Political Violence, 32(3), 506–538. https://doi.org/10.1080/09546553.2017.1385457
- Windsor, L. (2018). QuantText. https://quanttext.com
- Zhao, F., & Tung, A. K. H. (2012). Large scale cohesive subgraphs discovery for social network visual analysis. Proceedings of the VLDB Endowment, 6(2), 85–96. http://dl.acm.org/citation.cfm?id=2448936.2448942