Narrative Style Influences Citation Frequency in Climate Change Science

Ann Hillier; Ryan P. Kelly; Terrie Klinger

2016

• narrative analysis
• narrative research
• climate science
• Climate Change
• expository writing

From a sample of 732 scientific abstracts drawn from the climate change literature, we find that articles with more narrative abstracts are cited more often

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Summary

Introduction

• Climate change is among the most compelling issues confronting science and society, and climate science as a research endeavor has grown over the past decade.
• It is increasingly important that individual articles be presented in a way that facilitates the uptake of climate science and increases the salience of their individual research contributions.
• Evidence from psychology and literary theory suggests that audiences better understand and remember narrative writing in comparison with expository writing [2,3], and new evidence from neuroscience has revealed a specific region in the brain that is activated by stories [4].
• Narrative writing tells a story through related events [5], whereas expository writing relates facts without much social context.
• Presenting the same information in a more narrative way has the potential to increase its uptake—an especially attractive prospect in the context of climate science and scientific writing generally—and narratives are widely recognized as powerful tools of communication [2,6]

Methods

• Methods Abstract
  
  Selection
  
  We analyzed abstracts instead of the full text of selected papers because the abstract typically is the first section of the paper viewed by readers; the abstract is the only section of the paper immediately available on databases such as PubMed [22].
• We reasoned that it takes a number of years for papers to accrue a number of citations—and for a set of papers to develop a distribution of citation counts—that would allow us to test our core hypothesis.
• We began this study in 2015, and chose 5-to-6 years as a reasonable window, allowing for citations to accrue, but not letting the papers become outdated.
• Knowing that citations accrue to individual papers nonlinearly over time, we recognized the difficulty in using the available data to derive time-correction factors for each paper in the dataset.
• We featured only papers from a narrow time window, minimizing the effect of time-since-publication on the distribution of citations in our dataset

Results

• Individual Indicators of Narrativity
  
  Four of six narrative elements were positively associated with article citation frequency (Fig 1).
• Following ordination of the six narrative elements using PCA, PC1 served as our index of narrativity, and was significantly correlated with log(citations) (R2 = 0.05, p = 10−9; Fig 1).
• PC1 (Narrativity index) varied significantly among journals (p = 10−15), and correlated strongly and positively with log journal impact factor (R2 = 0.62, p = 6 x 10−5; carried out on PC1 journal means to avoid pseudoreplication), such that higher-impact journals tended to have more narrative articles (Fig 2).
• We found no citation effect for abstract length after accounting for journal; papers with more authors had subtly, but significantly, more citations than those with fewer authors even after controlling for journal (log(N authors), p < 10−6; each additional author was associated with an additional 0.4 citations in the dataset).

Conclusion

• Our results reveal that—at least among the set of peer-reviewed climate change literature included in our dataset—articles featuring more narrative writing styles are more often cited.
• This effect is independent of year of publication, number of authors, or abstract length.
• Of the narrative elements we tested for, the use of sensory language, conjunctions, connectivity between sentences, and appeal to the reader all positively and significantly influenced citation frequency.
• Of these four attributes, appeal [i.e., to the reader] is perhaps most broadly construed and least understood.
• It could be the case that appeal is positively associated with narrativity because, in the context of climate science, authors are likely to offer a recommendation that is identifiable to or understood by the reader

References

• 1. Haunschild R, Bornmann L, Marx W. Climate Change Research in View of Bibliometrics. PLoS ONE. 2016; 11: e0160393. doi: 10.1371/journal.pone.0160393 PMID: 27472663              ↩
• 2. Graesser AC, Olde B, Klettke B, Green M, Strange J, Brock T. How does the mind construct and represent stories? Narrative Impact: Social and cognitive foundations. Hoboken: Taylor & Francis; 2002. pp. 229–262.     ↩
• 3. Bower GH, Clark MC. Narrative stories as mediators for serial learning. Psychon Sci. 1969; 14: 181– 182.              ↩
• 4. Glasser MF, Coalson TS, Robinson EC, Hacker CD, Harwell J, Yacoub E, et al. A multi-modal parcellation of human cerebral cortex. Nature. 2016; 536: 171–178. doi: 10.1038/nature18933 PMID: 27437579              ↩
• 5. Abbott H. The Cambridge Introduction to Narrative. Cambridge, UK; New York, NY, USA: Cambridge University Press; 2002.     ↩
• 6. Dahlstrom MF. Using narratives and storytelling to communicate science with nonexpert audiences. Proc Natl Acad Sci U S A. 2014; 111: 13614–13620. doi: 10.1073/pnas.1320645111 PMID: 25225368              ↩
• 7. Bruner JS. Actual Minds, Possible Worlds. Cambridge, Mass.: Harvard University Press; 1986.     ↩
• 8. Muurlink O, McAllister P. Narrative risks in science writing for the lay public. J Sci Commun. 2015; 14: A01–1.              ↩
• 9. McBeth MK, Shanahan EA, Hathaway PL, Tigert LE, Sampson LJ. Buffalo tales: interest group policy stories in Greater Yellowstone. Policy Sci. 2010; 43: 391–409.              ↩
• 10. Spoel P, Goforth D, Cheu H, Pearson D. Public Communication of Climate Change Science: Engaging Citizens Through Apocalyptic Narrative Explanation. Tech Commun Q. 2008; 18: 49–81.              ↩
• 11. Kelly RP, Cooley SR, Klinger T. Narratives can motivate environmental action: the Whiskey Creek ocean acidification story. Ambio. 2014; 43: 592–9. doi: 10.1007/s13280-013-0442-2 PMID: 24081705              ↩
• 12. Jones MD. Cultural Characters and Climate Change: How Heroes Shape Our Perception of Climate Science: Cultural Characters and Climate Change. Soc Sci Q. 2014; 95: 1–39.              ↩
• 13. Paschen J-A, Ison R. Narrative research in climate change adaptation—Exploring a complementary paradigm for research and governance. Res Policy. 2014; 43: 1083–1092.              ↩
• 14. Herman D, Jahn M, Ryan M-L. Routledge encyclopedia of narrative theory. London: New York: Routledge; 2005.     ↩
• 15. Lejano R, Ingram M, Ingram H. The Power of Narrative in Env. Networks, ch. 3. 2013.              ↩
• 16. Bilandzic H, Dahlstrom M, Busselle R, Wagner A. Exemplars, anecdotes or narratives? A meta—analysis of narrativity in exemplification research and narrative persuasion. 2014.     ↩
• 17. Sydserff R, Weetman P. A texture index for evaluating accounting narratives: An alternative to readability formulas. Account Audit Account J. 1999; 12: 459–488.              ↩
• 18. Brunye TT, Ditman T, Mahoney CR, Augustyn JS, Taylor HA. When you and I share perspectives pronouns modulate perspective taking during narrative comprehension. Psychol Sci. 2009; 20: 27–32. doi: 10.1111/j.1467-9280.2008.02249.x PMID: 19076318              ↩
• 19. Mano Y, Harada T, Sugiura M, Saito DN, Sadato N. Perspective-taking as part of narrative comprehension: A functional MRI study. Neuropsychologia. 2009; 47: 813–824. doi: 10.1016/j.neuropsychologia. 2008.12.011 PMID: 19135072              ↩
• 20. Holstein J, Gubrium JF. Varieties of narrative analysis. Los Angeles [Calif.]: Sage; 2012.     ↩
• 21. Daiute C, Lightfoot C. Narrative analysis studying the development of individuals in society. Thousand Oaks, Calif: Sage; 2004.     ↩
• 22. Andrade C. How to write a good abstract for a scientific paper or conference presentation. Indian J Psychiatry. 2011; 53: 172. doi: 10.4103/0019-5545.82558 PMID: 21772657              ↩
• 23. Wechsler D. Crowdsourcing as a method of transdisciplinary research—Tapping the full potential of participants. Futures. 2014; 60: 14–22.     ↩
• 24. De Clercq O, Hoste V, Desmet B, Van Oosten P, De Cock M, Macken L. Using the Crowd for Readability Prediction. Nat Lang Eng. 2014; 1: 59.     ↩
• 25. Behrend TS, Sharek DJ, Meade AW, Wiebe EN. The viability of crowdsourcing for survey research. Behav Res Methods. 2011; 43: 800–813. doi: 10.3758/s13428-011-0081-0 PMID: 21437749              ↩
• 26. Gross AG, Harmon JE, Reidy M. Communicating Science: The Scientific Article from the 17th Century to the Present. New York, NY: Oxford University Press; 2002.     ↩
• 27. Dahlstrom MF. The moderating influence of narrative causality as an untapped pool of variance for narrative persuasion. Commun Res. 2015; 42: 779–795.              ↩
• 28. Fisher WR. Narrative rationality and the logic of scientific discourse. Argumentation. 1994; 8: 21–32.              ↩
• 29. Peterson EE, Langellier KM. The performance turn in narrative studies. Narrat Inq. 2006; 16: 173–180.              ↩
• 30. Fisher WR. Narrative rationality and the logic of scientific discourse. Argumentation. 1994; 8: 21–32.              ↩
• 31. Peterson EE, Langellier KM. The performance turn in narrative studies. Narrat Inq. 2006; 16: 173–180.              ↩
• 32. Norris SP, Guilbert SM, Smith ML, Hakimelahi S, Phillips LM. A theoretical framework for narrative explanation in science. Sci Educ. 2005; 89: 535–563.              ↩
• 33. Andrews M, Squire C, Tamboukou M. Doing narrative research. Los Angeles [Calif.]: London: SAGE; 2008.     ↩
• 34. Tijssen RJW. Net Citation Balances: A Measure of Influence between Scientific Journals. Science. 1990; 41: 298–304.              ↩
• 35. Weinberger CJ, Evans J, Allesina S. Ten Simple (Empirical) Rules for Writing Science. PLOS Comput Biol. 2015; 11: e1004205. doi: 10.1371/journal.pcbi.1004205 PMID: 25928031              ↩
• 36. Lawani S, Bayer A. Validity of citation criteria for assessing the influence of scientific publications: new evidence with peer assessment. J Am Soc Inf Sci. 1983; 34: 59–66.              ↩
• 37. Hurley LA, Ogier AL, Torvik VI. Deconstructing the collaborative impact: Article and author characteristics that influence citation count. Proc ASIST Annu Meet. 2013;50.              ↩
• 38. Hirsch JE. An index to quantify an individual’s scientific research output. Proc Natl Acad Sci U S A. 2005; 102: 16569–16572. doi: 10.1073/pnas.0507655102 PMID: 16275915              ↩
• 39. R Core Team. R: A language and environment for statistical computing. [Internet]. R Foundation for Statistical Computing, Vienna, Austria.; 2014. http://www.R-project.org/      ↩