特別報導 |《Journal of Data and Information Science》2021年第2期薦讀

Male, Female, and Nonbinary Differences in UK Twitter Self-descriptions: A Fine-grained Systematic ExplorationMike Thelwall, Saheeda Thelwall, RuthFaircloughPurpose:Although gender identities influence how people present themselves on socialmedia, previous studies have tested pre-specified dimensions of difference,potentially overlooking other differences and ignoring nonbinary users.Design/methodology/approach: Wordassociation thematic analysis was used to systematically check for fine-grainedstatistically significant gender differences in Twitter profile descriptionsbetween 409,487 UK-based female, male, and nonbinary users in 2020. A series ofstatistical tests systematically identified 1,474 differences at the individualword level, and a follow up thematic analysis grouped these words into themes.Findings:The results reflect offline variations in interests and in jobs. They also showdifferences in personal disclosures, as reflected by words, with femalesmentioning qualifications, relationships, pets, and illnesses much more,nonbinaries discussing sexuality more, and males declaring political and sportsaffiliations more. Other themes were internally imbalanced, including personalappearance (e.g. male: beardy; female: redhead), self-evaluations (e.g. male:legend; nonbinary: witch; female: feisty), and gender identity (e.g. male:dude; nonbinary: enby; female: queen).Research limitations: The methods are affected by linguistic styles and probablyunder-report nonbinary differences.Practical implications: The gender differences found may inform gender theory, and aidsocial web communicators and marketers.Originality/value: The results show a much wider range of gender expression differencesthan previously acknowledged for any social media site.「Sparking」 and 「Igniting」 Key Publications of 2020 Nobel Prize LaureatesFangjie Xi, Ronald Rousseau, Xiaojun HuPurpose: Thisarticle aims to determine the percentage of 「Sparking」 articles among the workof this year's Nobel Prize winners in medicine, physics, and chemistry.
Design/methodology/approach: We focus on under-cited influentialresearch among the key publications as mentioned by the Nobel Prize Committeefor the 2020 Noble Prize laureates. Specifically, we extracted data from theWeb of Science, and calculated the Sparking Indices using the formulas asproposed by Hu and Rousseau in 2016 and 2017. In addition, we identified anothertype of igniting articles based on the notion in 2017.
Findings: In the fields of medicine and physics, the proportions ofarticles with sparking characteristics share 78.571% and 68.75% respectively,yet, in chemistry 90% articles characterized by 「igniting」. Moreover, the twotypes of articles share more than 93% in the work of the Nobel Prize includedin this study.
Research limitations: Our research did not cover the impact oftopic, socio-political, and author's reputation on the Sparking Indices.
Practical implications: Our study shows that the Sparking Indicestruly reflect influence of the best research work, so it can be used to detectunder-cited influential articles, as well as identifying fundamental work.
Originality/value: Our findings suggest that the Sparking Indiceshave good applicability for research evaluation.Lone Geniuses or One among Many? An Explorative Study of Contemporary Highly Cited ResearchersDag W. Aksnes, Kaare AagaardPurpose: Theranking lists of highly cited researchers receive much public attention. Incommon interpretations, highly cited researchers are perceived to have madeextraordinary contributions to science. Thus, the metrics of highly citedresearchers are often linked to notions of breakthroughs, scientificexcellence, and lone geniuses.
Design/methodology/approach: In this study, we analyze a sample ofindividuals who appear on Clarivate Analytics' Highly CitedResearchers list. The main purpose is to juxtapose the characteristics of theirresearch performance against the claim that the list captures a small fractionof the researcher population that contributes disproportionately to extendingthe frontier and gaining—on behalf of society—knowledge and innovations thatmake the world healthier, richer, sustainable, and more secure.
Findings: The study reveals that the highly cited articles of theselected individuals generally have a very large number of authors. Thus, thesepapers seldom represent individual contributions but rather are the result oflarge collective research efforts conducted in research consortia. Thischallenges the common perception of highly cited researchers as individualgeniuses who can be singled out for their extraordinary contributions.Moreover, the study indicates that a few of the individuals have not evencontributed to highly cited original research but rather to reviews or clinicalguidelines. Finally, the large number of authors of the papers implies that theranking list is very sensitive to the specific method used for allocatingpapers and citations to individuals. In the 「whole count」 methodology appliedby Clarivate Analytics, each author gets full credit of the papersregardless of the number of additional co-authors. The study shows that theranking list would look very different using an alternative fractionalisedmethodology.
Research limitations: The study is based on a limited part of thetotal population of highly cited researchers.
Practical implications: It is concluded that 「excellence」understood as highly cited encompasses very different types of research andresearchers of which many do not fit with dominant preconceptions.
Originality/value: The study develops further knowledge on highlycited researchers, addressing questions such as who becomes highly cited andthe type of research that benefits by defining excellence in terms of citationscores and specific counting methods.Are University Rankings Statistically Significant? A Comparison among Chinese Universities and with the USALoet Leydesdorff, Caroline S. Wagner, LinZhangPurpose: Buildingon Leydesdorff, Bornmann, and Mingers (2019), we elaborate the differencesbetween Tsinghua and Zhejiang University as an empirical example. We addressthe question of whether differences are statistically significant in therankings of Chinese universities. We propose methods for measuring statisticalsignificance among different universities within or among countries.
Design/methodology/approach: Based on z-testing andoverlapping confidence intervals, and using data about 205 Chinese universitiesincluded in the Leiden Rankings 2020, we argue that three main groups ofChinese research universities can be distinguished (low, middle, and high).
Findings: When the sample of 205 Chinese universities is mergedwith the 197 US universities included in Leiden Rankings 2020, the resultssimilarly indicate three main groups: low, middle, and high. Using this data(Leiden Rankings and Web of Science), the z-scores of the Chineseuniversities are significantly below those of the US universities albeit withsome overlap.
Research limitations: We show empirically that differences inranking may be due to changes in the data, the models, or the modeling effectson the data. The scientometric groupings are not always stable when we usedifferent methods.
Practical implications: Differences among universities can betested for their statistical significance. The statistics relativize the valuesof decimals in the rankings. One can operate with a scheme of low/middle/highin policy debates and leave the more fine-grained rankings of individualuniversities to operational management and local settings.
Originality/value: In the discussion about the rankings ofuniversities, the question of whether differences are statisticallysignificant, has, in our opinion, insufficiently been addressed in researchevaluations.Identifying Scientific and Technical「Unicorns」Lucy L. Xu, Miao Qi, Fred Y. YePurpose: Usingthe metaphor of 「unicorn,」 we identify the scientific papers and technicalpatents characterized by the informetric feature of very high citations in thefirst ten years after publishing, which may provide a new pattern to understandvery high impact works in science and technology.
Design/methodology/approach: When we set CT as thetotal citations of papers or patents in the first ten years after publication,with CT≥ 5,000 for scientific 「unicorn」 and CT≥ 500 fortechnical 「unicorn,」 we have an absolute standard for identifying scientific andtechnical 「unicorn」 publications.
Findings: We identify 165 scientific 「unicorns」 in 14,301,875 WoSpapers and 224 technical 「unicorns」 in 13,728,950 DII patents during 2001-2012.About 50% of 「unicorns」 belong to biomedicine, in which selected cases areindividually discussed. The rare 「unicorns」 increase following linear model,the fitting data show 95% confidence with the RMSE of scientific 「unicorn」 is0.2127 while the RMSE of technical 「unicorn」 is 0.0923.
Research limitations: A 「unicorn」 is a pure quantitativeconsideration without concerning its quality, and 「potential unicorns」 as CT≤5,000for papers and CT≤500 for patents are left in future studies.
Practical implications: Scientific and technical 「unicorns」 providea new pattern to understand high-impact works in science and technology. The「unicorn」 pattern supplies a concise approach to identify very high-impactscientific papers and technical patents.
Originality/value: The 「unicorn」 pattern supplies a conciseapproach to identify very high impact scientific papers and technical patents.A Scientometric Study of Digital Literacy,ICT Literacy, Information Literacy, and Media LiteracyHyejin Park, Han Sung Kim, Han Woo ParkPurpose: Digitalliteracy and related fields have received interests from scholars andpractitioners for more than 20 years; nonetheless, academic communities need tosystematically review how the fields have developed. This study aims toinvestigate the research trends of digital literacy and related concepts sincethe year of 2000, especially in education.
Design/methodology/approach: The current study analyzes keywords,co-authorship, and cited publications in digital literacy through thescientometric method. The journal articles have been retrieved from the WoS(Web of Science) using four keywords: 「Digital literacy,」 「ICT literacy,」「information literacy,」 and 「media literacy.」 Further, keywords, publications,and co-authorship are examined and further classified into clusters for morein-depth investigation.
Findings: Digital literacy is a multidisciplinary field that widelyembraces literacy, ICT, the Internet, computer skill proficiency, science,nursing, health, and language education. The participants, or study subjects,in digital literacy research range from primary students to professionals, andthe co-authorship clusters are distinctive by countries in America and Europe.
Research limitations: This paper analyzes one fixed chunk of adataset obtained by searching for all four keywords at once. Further studieswill retrieve the data from diverse disciplines and will trace the change ofthe leading research themes by time spans.
Practical implications: To shed light on the findings, usingcustomized digital literacy curriculums and technology is critical for learnersat different ages to nurture digital literacy according to their learning aims.They need to cultivate their understanding of the social impact of exploitingtechnology and computational thinking. To increase the originality of digitalliteracy-related studies, researchers from different countries and cultures maycollaborate to investigate a broader range of digital literacy environments.
Originality/value: The present study reviews research trends indigital literacy and related areas by performing a scientometric study toanalyze multidimensional aspects in the fields, including keywords, journaltitles, co-authorship, and cited publications.A Causal Configuration Analysis of Payment Decision Drivers in Paid Q&AWenyu Chen, Yan Cheng, Jia LiPurpose: Thispaper examines factors of payment decision as well as the role each factorplays in casual configurations leading to high payment intention undersystematic and heuristic information processing routes.
Design/methodology/approach: Based on heuristic-systematic model(HSM), we propose a configurational analytic framework to investigate complexcasual relationships between influencing factors and payment decision. In linewith this approach, we use fuzzy-set qualitative comparative analysis (fsQCA)to analyze data crawled from Zhihu.com.
Findings: The number of previous consultations is a necessaryelement in all five equivalent configurations which lead to high intention inpayment decision. The heuristic processing route plays a core role while thesystematic processing route plays a peripheral role in payment decision-makingprocess.
Research limitations: Research is limited in that moderating effectof professional fields has not been considered in the framework.
Practical implications: Configurations in results can assistmanagers of knowledge communities and paid Q&A service providers in themanagement of information elements to motivate more payment decision.
Originality/value: This paper is one of the few studies to applyHSM theory and fsQCA method with respect to the payment decision in paidQ&A.Overview of Trends in Global Single Cell Research Based on Bibliometric Analysis and LDA Model (2009-2019)Tian Jiang, Xiaoping Liu, Chao Zhang,Chuanhao Yin, Huizhou LiuPurpose: Thisarticle aims to describe the global research profile and the development trendsof single cell research from the perspective of bibliometric analysis andsemantic mining.
Design/methodology/approach: The literatures on single cellresearch were extracted from Clarivate Analytic's Web of Science CoreCollection between 2009 and 2019. Firstly, bibliometric analyses were performedwith Thomson Data Analyzer (TDA). Secondly, topic identification and evolutiontrends of single cell research was conducted through the LDA topic model.Thirdly, taking the post-discretized method which is used for topic evolutionanalysis for reference, the topics were also be dispersed to countries todetect the spatial distribution.
Findings: The publication of single cell research showssignificantly increasing tendency in the last decade. The topics of single cellresearch field can be divided into three categories, which respectively refersto single cell research methods, mechanism of biological process, and clinicalapplication of single cell technologies. The different trends of thesecategories indicate that technological innovation drives the development ofapplied research. The continuous and rapid growth of the topic strength in thefield of cancer diagnosis and treatment indicates that thisresearch topic has received extensive attention in recent years. The topicdistributions of some countries are relatively balanced, while for the othercountries, several topics show significant superiority.
Research limitations: The analyzed data of this study only containthose were included in the Web of Science Core Collection.
Practical implications: This study provides insights into theresearch progress regarding single cell field and identifies the most concernedtopics which reflect potential opportunities and challenges. The national topicdistribution analysis based on the post-discretized analysis method extendstopic analysis from time dimension to space dimension.
Originality/value: This paper combines bibliometric analysis andLDA model to analyze the evolution trends of single cell research field. Themethod of extending post-discretized analysis from time dimension to spacedimension is distinctive and insightful.

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