A simulation-based analysis of the impact of rhetorical citations in science.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
10 Jan 2024
10 Jan 2024
Historique:
received:
24
04
2023
accepted:
05
12
2023
medline:
11
1
2024
pubmed:
11
1
2024
entrez:
10
1
2024
Statut:
epublish
Résumé
Authors of scientific papers are usually encouraged to cite works that meaningfully influenced their research (substantive citations) and avoid citing works that had no meaningful influence (rhetorical citations). Rhetorical citations are assumed to degrade incentives for good work and benefit prominent papers and researchers. Here, we explore if rhetorical citations have some plausibly positive effects for science and disproportionately benefit the less prominent papers and researchers. We developed a set of agent-based models where agents can cite substantively and rhetorically. Agents first choose papers to read based on their expected quality, become influenced by those that are sufficiently good, and substantively cite them. Next, agents fill any remaining slots in their reference lists with rhetorical citations that support their narrative, regardless of whether they were actually influential. We then turned agents' ability to cite rhetorically on-and-off to measure its effects. Enabling rhetorical citing increased the correlation between paper quality and citations, increased citation churn, and reduced citation inequality. This occurred because rhetorical citing redistributed some citations from a stable set of elite-quality papers to a more dynamic set with high-to-moderate quality and high rhetorical value. Increasing the size of reference lists, often seen as an undesirable trend, amplified the effects. Overall, rhetorical citing may help deconcentrate attention and make it easier to displace established ideas.
Identifiants
pubmed: 38200080
doi: 10.1038/s41467-023-44249-0
pii: 10.1038/s41467-023-44249-0
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
431Informations de copyright
© 2024. The Author(s).
Références
Baldi, S. Normative versus social constructivist processes in the allocation of citations: a network-analytic model. Am. Sociol. Rev. 63, 829–846 (1998).
Zuckerman, H. Citation analysis and the complex problem of intellectual influence. Scientometrics 12, 329–338 (1987).
doi: 10.1007/BF02016675
Leahey, E., Lee, J. & Funk, R. J. What types of novelty are most disruptive? Am. Sociol. Rev. 88, 562–597 (2023).
doi: 10.1177/00031224231168074
Bornmann, L. & Daniel, H. D. What do citation counts measure? A review of studies on citing behavior. J. Doc. 64, 45–80 (2008).
Gilbert, G. N. Referencing as persuasion. Soc. Stud. Sci. 7, 113–122 (1977).
doi: 10.1177/030631277700700112
Cozzens, S. What do citations count? The rhetoric-first model. Scientometrics 15, 437–447 (1989).
doi: 10.1007/BF02017064
Latour, B. & Woolgar, S. Laboratory Life: The Construction of Scientific Facts (Princeton University Press, 2013).
Nicolaisen, J. Citation analysis. Annu. Rev. Inf. Sci. Technol. 41, 609–641 (2007).
doi: 10.1002/aris.2007.1440410120
Teplitskiy, M., Duede, E., Menietti, M. & Lakhani, K. R. How status of research papers affects the way they are read and cited. Res. Policy 51, 104484 (2022).
doi: 10.1016/j.respol.2022.104484
Allen, B. Referring to schools of thought: an example of symbolic citations. Soc. Stud. Sci. 27, 937–949 (1997).
doi: 10.1177/030631297027006004
Catalini, C., Lacetera, N. & Oettl, A. The incidence and role of negative citations in science. Proc. Natl Acad. Sci. USA 112, 13823–13826 (2015).
pubmed: 26504239
pmcid: 4653214
doi: 10.1073/pnas.1502280112
Wilhite, A. W. & Fong, E. A. Coercive citation in academic publishing. Science 335, 542–543 (2012).
pubmed: 22301307
doi: 10.1126/science.1212540
Cobb, C. L., Crumly, B., Montero-Zamora, P., Schwartz, S. J., & Martínez Jr, C. R. The problem of miscitation in psychological science: righting the ship. Am. Psychol. (2023).
Rubin, A. & Rubin, E. Systematic bias in the progress of research. J. Political Econ. 129, 2666–2719 (2021).
doi: 10.1086/715021
White, H. Reward, persuasion, and the Sokal Hoax: a study in citation identities. Scientometrics 60, 93–120 (2004).
doi: 10.1023/B:SCIE.0000027313.91401.9b
Frandsen, T. F. & Nicolaisen, J. Citation behavior: a large-scale test of the persuasion by name-dropping hypothesis. J. Assoc. Inf. Sci. Technol. 68, 1278–1284 (2017).
doi: 10.1002/asi.23746
Penders, B. Ten simple rules for responsible referencing. PLoS Comput. Biol. 14, e1006036 (2018).
pubmed: 29649210
pmcid: 5896885
doi: 10.1371/journal.pcbi.1006036
Nature Genetics Editorials. Neutral citation is poor scholarship. Nat. Genet. 49, 1559 (2017).
doi: 10.1038/ng.3989
Petrić, B. Rhetorical functions of citations in high-and low-rated master’s theses. J. Engl. Acad. Purp. 6, 238–253 (2007).
doi: 10.1016/j.jeap.2007.09.002
Rose, R. What’s love got to do with it? Dev. Pract. 40, 3–5 (2014).
Hoppe, T. A., Arabi, S. & Hutchins, B. I. Predicting substantive biomedical citations without full text. Proc. Natl Acad. Sci. USA 120, e2213697120 (2023).
pubmed: 37463199
pmcid: 10372685
doi: 10.1073/pnas.2213697120
Kozlowski, D., Andersen, J. P. & Larivière, V. Uncited articles and their effect on the concentration of citations. arXiv preprint arXiv:2306.09911 (2023).
Cronin, B. The need for a theory of citing. J. Doc. 37, 16–24 (1981).
Tahamtan, I. & Bornmann, L. What do citation counts measure? An updated review of studies on citations in scientific documents published between 2006 and 2018. Scientometrics 121, 1635–1684 (2019).
doi: 10.1007/s11192-019-03243-4
Tahamtan, I. & Bornmann, L. The social systems citation theory (SSCT): a proposal to use the social systems theory for conceptualizing publications and their citations links. Prof. Inf. 31, e310411 (2022).
Jurgens, D., Kumar, S., Hoover, R., McFarland, D. & Jurafsky, D. Measuring the evolution of a scientific field through citation frames. Trans. Assoc. Comput. Linguist. 6, 391–406 (2018).
doi: 10.1162/tacl_a_00028
Nicholson, J. M. et al. SCITE: a smart citation index that displays the context of citations and classifies their intent using deep learning. Quant. Sci. Stud. 2, 882–898 (2021).
doi: 10.1162/qss_a_00146
Tenopir, C., King, D. W., Christian, L. & Volentine, R. Scholarly article seeking, reading, and use: a continuing evolution from print to electronic in the sciences and social sciences. Learn. Publ. 28, 93–105 (2015).
doi: 10.1087/20150203
Renear, A. H. & Palmer, C. L. Strategic reading, ontologies, and the future of scientific publishing. Science 325, 828–832 (2009).
pubmed: 19679805
doi: 10.1126/science.1157784
Wang, D., Song, C. & Barabási, A. L. Quantifying long-term scientific impact. Science 342, 127–132 (2013).
pubmed: 24092745
doi: 10.1126/science.1237825
Wang, P. & Domas White, M. A cognitive model of document use during a research project. Study II. Decisions at the reading and citing stages. J. Am. Soc. Inf. Sci. 50, 98–114 (1999).
doi: 10.1002/(SICI)1097-4571(1999)50:2<98::AID-ASI2>3.0.CO;2-L
Lerman, K., Hodas, N., & Wu, H. (2017). Bounded rationality in scholarly knowledge discovery. arXiv preprint arXiv:1710.00269.
Petersen, A. M. et al. Reputation and impact in academic careers. Proc. Natl Acad. Sci. USA 111, 15316–15321 (2014).
Simcoe, T. S. & Waguespack, D. M. Status, quality, and attention: what’s in a (missing) name? Manag. Sci. 57, 274–290 (2010).
doi: 10.1287/mnsc.1100.1270
Wang, P. & Soergel, D. A cognitive model of document use during a research project. Study I. Document selection. J. Am. Soc. Inf. Sci. 49, 115–133 (1998).
doi: 10.1002/(SICI)1097-4571(199802)49:2<115::AID-ASI3>3.0.CO;2-T
Azoulay, P., Stuart, T. & Wang, Y. Matthew: effect or fable? Manag. Sci. 60, 92–109 (2013).
doi: 10.1287/mnsc.2013.1755
Milard, B. & Tanguy, L. Citations in scientific texts: do social relations matter? J. Assoc. Inf. Sci. Technol. 69, 1380–1395 (2018).
doi: 10.1002/asi.24061
Murray, S. O. & Poolman, R. C. Strong ties and scientific literature. Soc. Netw. 4, 225–232 (1982).
doi: 10.1016/0378-8733(82)90023-5
Merton, R. K. The Sociology of Science: Theoretical and Empirical Investigations (University of Chicago Press, 1973)
Horbach, S., Aagaard, K. & Schneider, J. W. Meta-research: how problematic citing practices distort science. MetaArXiv https://doi.org/10.31222/osf.io/aqyhg (2021).
Leigh Star, S This is not a boundary object: reflections on the origin of a concept. Sci. Technol. Hum. Values 35, 601–617 (2010).
doi: 10.1177/0162243910377624
Mizruchi, M. S. & Fein, L. C. The social construction of organizational knowledge: a study of the uses of coercive, mimetic, and normative isomorphism. Adm. Sci. Q. 44, 653–683 (1999).
doi: 10.2307/2667051
Rekdal, O. B. Academic urban legends. Soc. Stud. Sci. 44, 638–654 (2014).
pubmed: 25272616
pmcid: 4232290
doi: 10.1177/0306312714535679
Hargens, L. L. Using the literature: reference networks, reference contexts, and the social structure of scholarship. Am. Sociol. Rev. 65, 846–865 (2000).
doi: 10.1177/000312240006500603
Shwed, U. & Bearman, P. S. The temporal structure of scientific consensus formation. Am. Sociol. Rev. 75, 817–840 (2010).
pubmed: 21886269
pmcid: 3163460
doi: 10.1177/0003122410388488
Beel, J. & Gipp, B. Google Scholar’s ranking algorithm: the impact of citation counts (an empirical study). In Flory, A. & Collard, M. (Eds.), 2009 Third International Conference on Research Challenges in Information Science 439–446 (IEEE, 2009).
Latour, B. Science in Action: How to Follow Scientists and Engineers through Society (Harvard University Press, 1987).
Lin, Y., Evans, J. A. & Wu, L. New directions in science emerge from disconnection and discord. J. Informetr. 16, 101234 (2022).
doi: 10.1016/j.joi.2021.101234
Wu, L., Wang, D. & Evans, J. A. Large teams develop and small teams disrupt science and technology. Nature 566, 378–382 (2019).
pubmed: 30760923
doi: 10.1038/s41586-019-0941-9
Chu, J. S. & Evans, J. A. Slowed canonical progress in large fields of science. Proc. Natl Acad. Sci. USA 118, e2021636118 (2021).
Evans, J. A. Electronic publication and the narrowing of science and scholarship. Science 321, 395–399 (2008).
pubmed: 18635800
doi: 10.1126/science.1150473
Park, M., Leahey, E. & Funk, R. J. Papers and patents are becoming less disruptive over time. Nature 613, 138–144 (2023).
pubmed: 36600070
doi: 10.1038/s41586-022-05543-x
Parolo, P. D. B. et al. Attention decay in science. J. Informetr. 9, 734–745 (2015).
doi: 10.1016/j.joi.2015.07.006
Price, D. J. Little Science, Big Science (Columbia University Press, 1963).
Nielsen, M. W. & Andersen, J. P. Global citation inequality is on the rise. Proc. Natl Acad Sci. USA 118, e2012208118 (2021).
Gomez, C. J., Herman, A. C. & Parigi, P. Leading countries in global science increasingly receive more citations than other countries doing similar research. Nat. Hum. Behav. 6, 919–929 (2022).
Feenberg, D., Ganguli, I., Gaule, P. & Gruber, J. It’s good to be first: Order bias in reading and citing NBER working papers. Rev. Econ. Stat. 99, 32–39 (2017).
doi: 10.1162/REST_a_00607
Andersen, J. P. Field-level differences in paper and author characteristics across all fields of science in Web of Science, 2000–2020. Quant. Sci. Stud. 4, 394–422 (2023).
Granovetter, M. Threshold models of collective behavior. Am. J. Sociol. 83, 1420–1443 (1978).
doi: 10.1086/226707
Centola, D. An experimental study of homophily in the adoption of health behavior. Science 334, 1269–1272 (2011).
pubmed: 22144624
doi: 10.1126/science.1207055
Greenberg, S. A. How citation distortions create unfounded authority: analysis of a citation network. BMJ 339, b2680 (2009).
Letrud, K. & Hernes, S. Affirmative citation bias in scientific myth debunking: A three-in-one case study. PLoS ONE 14, e0222213 (2019).
pubmed: 31498834
pmcid: 6733478
doi: 10.1371/journal.pone.0222213
De Vries, Y. A. et al. The cumulative effect of reporting and citation biases on the apparent efficacy of treatments: the case of depression. Psychol. Med. 48, 2453–2455 (2018).
pubmed: 30070192
pmcid: 6190062
doi: 10.1017/S0033291718001873
West, J. D. & Bergstrom, C. T. Misinformation in and about science. Proc. Natl Acad. Sci. USA 118, e1912444117 (2021).
pubmed: 33837146
pmcid: 8054004
doi: 10.1073/pnas.1912444117
Guetzkow, J., Lamont, M. & Mallard, G. What is originality in the humanities and the social sciences? Am. Sociol. Rev. 67, 190–212 (2004).
doi: 10.1177/000312240406900203
Bradley, K. J. & Aguinis, H. Team performance: nature and antecedents of nonnormal distributions. Organ. Sci. 34, 1266–1286 (2022).
Lancho-Barrantes, B. S., Guerrero-Bote, V. P. & Moya-Anegón, F. What lies behind the averages and significance of citation indicators in different disciplines? J. Inf. Sci. 36, 371–382 (2010).
doi: 10.1177/0165551510366077
Denrell, J. & Liu, C. When reinforcing processes generate an outcome-quality dip. Organ. Sci. 32, 1079–1099 (2021).
doi: 10.1287/orsc.2020.1414
van de Rijt, A. Self-correcting dynamics in social influence processes. Am. J. Sociol. 124, 1468–1495 (2019).
Zuckerman, E. W. Construction, concentration, and (dis) continuities in social valuations. Annu. Rev. Sociol. 38, 223–245 (2012).
doi: 10.1146/annurev-soc-070210-075241