计算机科学学术论文写作 (5).pdf

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1、RESEARCH ARTICLENarrative Style Influences Citation Frequencyin Climate Change ScienceAnn Hillier,Ryan P.Kelly*,Terrie KlingerSchool of Marine&Environmental Affairs,University of Washington,Seattle,Washington,United States ofAmerica*rpkellyuw.eduAbstractPeer-reviewed publications focusing on climate

2、 change are growing exponentially with theconsequence that the uptake and influence of individual papers varies greatly.Here,wederive metrics of narrativity from psychology and literary theory,and use these metrics totest the hypothesis that more narrative climate change writing is more likely to be

3、 influential,using citation frequency as a proxy for influence.From a sample of 732 scientific abstractsdrawn from the climate change literature,we find that articles with more narrative abstractsare cited more often.This effect is closely associated with journal identity:higher-impactjournals tend

4、to feature more narrative articles,and these articles tend to be cited moreoften.These results suggest that writing in a more narrative style increases the uptake andinfluence of articles in climate literature,and perhaps in scientific literature more broadly.IntroductionClimate change is among the

5、most compelling issues now confronting science and society,and climate science as a research endeavor has grown accordingly over the past decade.Thenumber of scholarly publications is increasing exponentially,doubling every 56 years 1.The volume of climate science publications now being produced far

6、 exceeds the ability of indi-vidual investigators to read,remember,and use.Accordingly,it is increasingly important thatindividual articles be presented in a way that facilitates the uptake of climate science andincreases the salience of their individual research contributions.Evidence from psycholo

7、gy and literary theory suggests that audiences better understandand remember narrative writing in comparison with expository writing 2,3,and new evi-dence from neuroscience has revealed a specific region in the brain that is activated by stories4.Narrative writing tells a story through related event

8、s 5,whereas expository writing relatesfacts without much social context.Presenting the same information in a more narrative wayhas the potential to increase its uptakean especially attractive prospect in the context of cli-mate science and scientific writing generallyand consequently,narratives are

9、widely recog-nized as powerful tools of communication 2,6.Despite this,professional scientific writing tends to be more expository than narrative,pri-oritizing objective observations made by detached researchers and relying on the logicalPLOS ONE|DOI:10.1371/journal.pone.0167983December 15,20161/12a

10、11111OPENACCESSCitation:HillierA,KellyRP,KlingerT(2016)NarrativeStyleInfluencesCitationFrequencyinClimateChangeScience.PLoSONE11(12):e0167983.doi:10.1371/journal.pone.0167983Editor:GaryS.Bilotta,UniversityofBrighton,UNITEDKINGDOMReceived:September7,2016Accepted:November23,2016Published:December15,20

11、16Copyright:2016Hillieretal.ThisisanopenaccessarticledistributedunderthetermsoftheCreativeCommonsAttributionLicense,whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalauthorandsourcearecredited.DataAvailabilityStatement:AllrelevantdataarewithinthepaperanditsSuppor

12、tingInformationfiles.Funding:Theauthorsreceivednospecificfundingforthiswork.CompetingInterests:Theauthorshavedeclaredthatnocompetinginterestsexist.proposition“if X,then Y”to define the structure of the argument 7.Narrative writing,on theother hand,is commonly used to good effect in popular science w

13、riting 8.Both simple narra-tives and apocalyptic climate narratives are known to capture public attention and spur action911.Moreover,narratives can influence perceptions of climate risk and policy preferencesamong the public 12,and the narrative style has been proposed as a powerful means ofresearc

14、h to address problems of knowledge,policy,and action as they relate to climate change13.Here we explore the influence of narrative in the professional communication of climatescience research,acknowledging that the perception of narrative can be subjective and con-text-dependent 14,15.We hypothesize

15、d that scientific papers with more narrative text aremore likely to be highly cited than those with less narrative(i.e.,more expository)text,usingcitation frequency as a proxy for a papers influence on the field at large.To test this hypothe-sis,we derived six elements of narrativity from studies on

16、 narrative comprehension 1517and the literatures of psychology 2,18,19 and narrative theory 14,20,21,and used these sixelements to evaluate the degree of narrativity in 732 abstracts taken from the peer-reviewedscientific literature on climate change.We then assessed the relationship between narrati

17、vityin these journal abstracts in the context of other factors known to influence citation rate,including journal identity,abstract length,and number of authors.MethodsAbstract SelectionWe analyzed abstracts instead of the full text of selected papers because the abstract typically isthe first secti

18、on of the paper viewed by readers;moreover,the abstract is the only section of thepaper immediately available on databases such as PubMed 22.Hence,abstracts provide a rel-atively consistent point of entry to scientific publications.To select focal abstracts for the data-set,we first used the PubMed

19、database to select the journals that published the largest numberof articles featuring the phrase“climate change”in the abstract or title between 2009 and 2010.Our reasoning for choosing the set of papers that we did was as follows:First,we limited thescope by the field of inquiry(climate change),ho

20、ping to minimize the statistical variance(or“noise”)that would probably have resulted from an analysis that included many fields(whichin turn likely differ in citation frequencies and writing conventions,among other relevant fac-tors).Next,we reasoned that it takes a number of years for papers to ac

21、crue a number of cita-tionsand consequently for a set of papers to develop a distribution of citation countsthatwould allow us to test our core hypothesis.We began this study in 2015,and chose 5-to-6years as a reasonable window,allowing for citations to accrue,but not letting the papersbecome outdat

22、ed.Finally,knowing that citations accrue to individual papers nonlinearly overtime,we recognized the difficulty in using the available data(total citations,rather than cita-tions-by-year for each paper)to derive time-correction factors for each paper in the dataset.Consequently,we featured only pape

23、rs from a narrow time window,minimizing the effect oftime-since-publication on the distribution of citations in our dataset.We identified 19 journals with the largest number of articles meeting these criteria,andthen retrieved the abstracts,citation counts,and other relevant information through the

24、data-base Web of Science(S1 Table;raw dataset N=802 abstracts;N=732 after quality control;seebelow).These abstracts differed in citation frequency by two orders of magnitude,having beencited between 1 and 1205 times as of March 30,2016(median=69;we did not collect data onpapers with zero citations i

25、n order to avoid the problems associated with log-transformingzero data),and reflected the expected left-skewed distribution.Narrative Style and CitationsPLOS ONE|DOI:10.1371/journal.pone.0167983December 15,20162/12CrowdsourcingWe used the crowdsourcing site CrowdFlower(http:/)to collect infor-matio

26、n regarding the narrativity of each abstract.Crowdsourcingin which many individualsare paid small amounts of money to complete discrete parts of a much larger taskas aresearch method is growing as technical capacity increases 23.It offers an efficient researchtool for work that requires a degree of

27、human assessment spread over a large number of datapoints,with access to a diverse,skilled workforce,and produces reliable data in comparisonwith alternative methods 24,25.The CrowdFlower platform allowed us to:1)collect reader-coded information for a largenumber of abstracts that could not be colle

28、cted by text-mining or other means;2)collect mul-tiple(n=7)independent assessments(“judgments”)about the narrativity of each abstract;andsimultaneously 3)include human interpretation and discretion in the quantification of narra-tivity.We collected multiple judgments for each abstract as a means of

29、quality-control,giventhat individual readers can perceive narrativity somewhat differently 26.Online contributors evaluated abstracts by first reading instructions(S1 Text)and an exam-ple question,and then answering a series of six questions(S2 Text)for each abstract.Thesequestions were intended to

30、evaluate each abstract with respect to indicators of narrativity(described in the next section).Contributors were paid per submitted page,each of whichincluded five abstracts and the corresponding questions.We used the following measures to ensure high quality responses:1)gave access to this jobonly

31、 to CrowdFlowers highest ranked contributors(the site ranks them based upon past per-formance);2)set a minimum completion time for each page of work;and 3)restricted contrib-utor location to a number of countries in which English is the primary language and literacyrates are high:Australia,Canada,Ne

32、w Zealand,United Kingdom,and United States.Althoughour primary reason for imposing this restriction was based on language skills,we note thatthese countries largely correspond to those that dominate climate change publications,both interms of number and citation frequency 1.A total of 155 individual

33、 contributors evaluatedthe abstracts used in this study.Independent Variables:Narrative IndicatorsTo derive indicators of narrativity,we adapted methods and indicators based on comparablestudies 1517 and supported by relevant literature from narrative theory 14,20,21,psychol-ogy 2,18,19,communicatio

34、ns 27,philosophy 28,and history 26.We chose indicators toreflect setting,narrative perspective,sensorylanguage,conjunctions,connectivity,and appeal.Setting provides a description of where and when events take place and is of the fundamen-tal components of narratives.The spatial and temporal dimensio

35、ns established by setting helpcreate a mental image that distinguishes narratives from other forms of discourse 20.Weassessed setting by asking contributors whether there is a specific mention of place or time inthe abstract 16.Narrative perspective describes the position or role of the narrator.Acc

36、ording to Lejanoet al.15,the presence of a narrator distinguishes narratives from other forms of communica-tionthat is,narrators tell narratives.The narrator is responsible for eliciting emotions in thereader 29.First-person narrators have a stronger narrative presence than other narrative per-spect

37、ives,such as third-person or no narrator 2,16.We assessed narrative perspective by ask-ing contributors whether or not the narrator referred to himself in the text(e.g.,through use ofpronouns such as I,we,and our).Sensorylanguage appeals to the senses and emotions of the reader and can be used to es

38、tab-lish personal identity,for example,through the narrator expressing“emotions,attitudes,Narrative Style and CitationsPLOS ONE|DOI:10.1371/journal.pone.0167983December 15,20163/12beliefs,and interpretations”20.Accordingly,we assessed sensory language by asking con-tributors to count the number of t

39、imes that sensory or emotional language appeared in theabstract.We then normalized the resulting counts by abstract length(number of words).Conjunctions are used to connect words and phrases,binding narratives together in a logicalform 17.We used the presence of conjunctions to determine the extent

40、to which an abstractis logically ordered,based on the observation that a temporal or causal ordering of events isan essential,and distinguishing,characteristic of narratives 15,3033,one which impliesmomentum towards completion 20 and evokes human understanding 21.We assessed theuse of conjunctions b

41、y asking contributors to count the number of times that conjunctions sig-nifying cause and effect,contrast,or temporal ordering appeared in the text.We then normal-ized the resulting counts by abstract length.Connectivity refers to words or phrases that create explicit links within the text,either a

42、s aspecific reference back to the same thing or repetition of a word from the previous sentence,provided it carries the same meaning 17.We assessed connectivity by asking contributors tocount the number of times that words or phrases from one sentence were used to create anexplicit link to the sente

43、nce immediately preceding it.We provided contributors the additionalinstruction to look for logical linkage between ideas.We then normalized the resulting countsby abstract length.Appeal refers to the moral or evaluative orientation of a narrative 22.Appeal in the formof evaluative commentary or lan

44、dscape of consciousness is an important aspect of narrativity14,21,answering the question of why the story is being told.We assessed the use of appeal byasking contributors if the text makes an explicit appeal to the reader or a clear recommenda-tion for action 16.Independent Variables:OtherIn addit

45、ion to the crowdsourced assessments of narrative elements,we collected informationon length of abstract(number of words),number of authors,year of publication,journal iden-tity,and journal impact factor.These factors are known to influence the citation rate of peer-reviewed literature 3436 and were

46、available via Web of Science for each abstract in thedataset.Dependent Variable:Citation FrequencyWe used citation frequency as a measure of article influence.A large body of literature sup-ports the use of citation analyses as frameworks for evaluating science communication 34,3638.Citations reflec

47、t the cumulative nature of science and the extent to which a piece of workis represented in a body of literature 36,and can therefore be used as to evaluate the degreeof influence of a publication on its field.We used Web of Science to establish the number ofcitations for the articles associated wit

48、h each abstract in our dataset.We log-transformed cita-tion counts to account for the skewed distribution in citations.Quality ControlWe treated Question 2,“Does the narrator refer to himself in the text?”as a“test”question,orsecondary quality-control mechanism,due to its objectivity(i.e.,unlike som

49、e of the other nar-rative indicators,the existence of a first-person narrator has a“true”answer).After consider-ing all seven responses for this question,respondents who answered in the majority wereincluded in the analysis,whereas respondents who answered in the minority were assumed tobe in error

50、and their responses were omitted entirely from the analysis.This improved ourconfidence in the responses and subsequent analysis.After omitting these minority responses,Narrative Style and CitationsPLOS ONE|DOI:10.1371/journal.pone.0167983December 15,20164/12we averaged the scores across remaining r