How do authors select keywords? A preliminary study of author keyword selection behavior

Abstract Author keywords for scientific literature are terms selected and created by authors. Although most studies have focused on how to apply author keywords to represent their research interests, little is known about the process of how authors select keywords. To fill this research gap, this study presents a pilot study on author keyword selection behavior. Our empirical results show that the average percentages of author keywords appearing in titles, abstracts, and both titles and abstracts are 31%, 52.1%, and 56.7%, respectively. Meanwhile, we find that keywords also appear in references and high-frequency keywords. The proportions of author-selected keywords appearing in the references and high-frequency keywords are 41.6% and 56.1%, respectively. In addition, keywords of papers written by core authors (productive authors) are found to appear less frequently in titles and abstracts in their papers than that of others, and appear more frequently in references and high-frequency keywords. The percentages of keywords appearing in titles and abstracts in scientific papers are negatively correlated with citation counts of papers. In contrast, the percentages of author keywords appearing in high-frequency keywords are positively associated with citation counts of papers.

[1]  Dora Sales,et al.  Scientific production on mobile information literacy in higher education: a bibliometric analysis (2006–2017) , 2019, Scientometrics.

[2]  Sheue-Ling Hwang,et al.  Analysis of keyword-based tagging behaviors of experts and novices , 2011, Online Inf. Rev..

[3]  Ronald N. Kostoff,et al.  How Useful are `Key Words' in Scientific Journals? , 2003, J. Inf. Sci..

[4]  Hassan Naderi,et al.  A model-based method to improve the quality of ranking in keyword search systems using pseudo-relevance feedback , 2019, J. Inf. Sci..

[5]  Xiaohua Hu,et al.  User tags versus expert-assigned subject terms: A comparison of LibraryThing tags and Library of Congress Subject Headings , 2010, J. Inf. Sci..

[6]  Sunyoung Kwon,et al.  Characteristics of interdisciplinary research in author keywords appearing in Korean journals , 2018, Malaysian Journal of Library & Information Science.

[7]  Sebastián Lozano,et al.  Complex network analysis of keywords co-occurrence in the recent efficiency analysis literature , 2019, Scientometrics.

[8]  Lawrence D. Fu,et al.  Using content-based and bibliometric features for machine learning models to predict citation counts in the biomedical literature , 2010, Scientometrics.

[9]  Isidoro Gil-Leiva,et al.  Keywords given by authors of scientific articles in database descriptors , 2007 .

[10]  Parveen Babbar,et al.  Occurrence of author keywords and keywords plus in social sciences and humanities research : A preliminary study , 2018, COLLNET Journal of Scientometrics and Information Management.

[11]  Munan Li Classifying and ranking topic terms based on a novel approach: role differentiation of author keywords , 2018, Scientometrics.

[12]  Jinbo Song,et al.  A review of emerging trends in global PPP research: analysis and visualization , 2016, Scientometrics.

[13]  Jiang Li,et al.  Innovation or imitation: The diffusion of citations , 2018, J. Assoc. Inf. Sci. Technol..

[14]  Ya-Ning Chen,et al.  Structure and pattern of social tags for keyword selection behaviors , 2012, Scientometrics.

[15]  A Comparative Analysis of English Abstracts and Summaries of Chinese Research Articles in Three Library and Information Science Journals Indexed by the Taiwan Social Science Citation Index , 2019 .

[16]  Hussein Meihami,et al.  Informetrics of Scientometrics abstracts: a rhetorical move analysis of the research abstracts published in Scientometrics journal , 2018, Scientometrics.

[17]  Loet Leydesdorff,et al.  Does the public discuss other topics on climate change than researchers? A comparison of networks based on author keywords and hashtags , 2018, J. Informetrics.

[18]  Chao Lu,et al.  Examining scientific writing styles from the perspective of linguistic complexity , 2018, J. Assoc. Inf. Sci. Technol..

[19]  Miguel A. Andrade-Navarro,et al.  Information extraction from full text scientific articles: Where are the keywords? , 2003, BMC Bioinformatics.

[20]  Muhammad Imran,et al.  Mapping past, current and future energy research trend in Pakistan: a scientometric assessment , 2018, Scientometrics.

[22]  Adam Fadlalla,et al.  A keyword-based organizing framework for ERP intellectual contributions , 2015, J. Enterp. Inf. Manag..

[23]  Bruce E. Trumbo,et al.  Key Words and Phrases—The Key to Scholarly Visibility and Efficiency in an Information Explosion , 1995 .

[24]  John Hudson,et al.  An analysis of the titles of papers submitted to the UK REF in 2014: authors, disciplines, and stylistic details , 2016, Scientometrics.

[25]  Hossein Amirkhani,et al.  Bibliometrics of sentiment analysis literature , 2019, J. Inf. Sci..

[26]  Lei Lei,et al.  Readability and citations in information science: evidence from abstracts and articles of four journals (2003–2012) , 2016, Scientometrics.

[27]  Feng Xia,et al.  Two decades of information systems: a bibliometric review , 2018, Scientometrics.

[28]  Kun Lu,et al.  How many keywords do authors assign to research articles – a multi-disciplinary analysis? , 2018 .

[29]  Hao-Ren Ke,et al.  A study on mental models of taggers and experts for article indexing based on analysis of keyword usage , 2014, J. Assoc. Inf. Sci. Technol..

[30]  Chao Ma,et al.  Succinct effect or informative effect: the relationship between title length and the number of citations , 2018, Scientometrics.

[31]  Arif Khan,et al.  A Framework to Explore the Knowledge Structure of Multidisciplinary Research Fields , 2015, PloS one.

[32]  Wei Lu,et al.  Functional structure identification of scientific documents in computer science , 2018, Scientometrics.

[33]  Leo Egghe An exact calculation of Price's law for the law of Lotka , 2005, Scientometrics.

[34]  Xu Jiang,et al.  A bibliometric analysis for global research trends on ectomycorrhizae over the past thirty years , 2018, Electron. Libr..

[35]  Jiming Hu,et al.  Research patterns and trends of Recommendation System in China using co-word analysis , 2015, Inf. Process. Manag..

[36]  Yang Xu,et al.  A quantitative exploration on reasons for citing articles from the perspective of cited authors , 2018, Scientometrics.

[37]  Sunyoung Park,et al.  Exploring human resource development research themes: A keyword network analysis , 2018, Human Resource Development Quarterly.

[38]  Arif Khan,et al.  The impact of author-selected keywords on citation counts , 2016, J. Informetrics.

[39]  Shuguang Han,et al.  Deep Keyphrase Generation , 2017, ACL.

[40]  Antonio Perianes-Rodríguez,et al.  Co-word analysis and thematic landscapes in Spanish information science literature, 1985–2014 , 2017, Scientometrics.

[41]  Schubert Foo,et al.  Using author-specified keywords in building an initial reading list of research papers in scientific paper retrieval and recommender systems , 2017, Inf. Process. Manag..

[42]  Lutz Bornmann,et al.  What do citation counts measure? A review of studies on citing behavior , 2008, J. Documentation.

[43]  Chien-wen Shen,et al.  Bibliometric networks and analytics on gerontology research , 2019, Libr. Hi Tech.

[44]  Margaret E. I. Kipp,et al.  Tagging of Biomedical Articles on CiteULike: A Comparison of User, Author and Professional Indexing , 2011 .

[45]  Dan Wu,et al.  Comparing social tags with subject headings on annotating books: A study comparing the information science domain in English and Chinese , 2013, J. Inf. Sci..

[46]  Chuan Wu,et al.  Keyphrase Extraction Based on Prior Knowledge , 2018, JCDL.