Tuesday, 9 April 2019

Which can better predict the future success of articles? Bibliometric indices or alternative metrics


Source: https://link.springer.com/article/10.1007/s11192-019-03052-9
Scientometrics
pp 1–21 | Cite as

Which can better predict the future success of articles? Bibliometric indices or alternative metrics

  • Mingyang Wang
  • Zhenyu Wang
  • Guangsheng ChenEmail author
  1. 1.College of Information and Computer EngineeringNortheast Forestry UniversityHarbinPeople’s Republic of China
Article
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Abstract

In this paper, we made a survey on the prediction capability of bibliometric indices and alternative metrics on the future success of articles by establishing a machine learning framework. Twenty-three bibliometric and alternative indices were collected to establish the feature space for the predication task. In order to eliminate the possible redundancy in feature space, three feature selection techniques of Relief-F, principal component analysis and entropy weighted method were used to rank the features according to their contribution to the original data set. Combining the fractal dimension of the data set, the intrinsic features which can better represent the original feature space were extracted. Three classifiers of Naïve Bayes, KNN and random forest were performed to detect the classification performance of these features. Experimental results show that both bibliometric indices and alternative metrics are beneficial to articles’ growth. Early citation features, early Web usage statistics, as well as the reputation of the first author are the most valuable indicators in making an article more influential in the future.

Keywords

Highly-cited papers Bibliometric index Alternative metrics Machine learning 
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Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 71473034), the financial assistance from Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province (Grant No. LBH-Q16003), and the national undergraduate training programs for innovation (Grant No. 201510225167).

Supplementary material

11192_2019_3052_MOESM1_ESM.docx (19 kb)
Supplementary material 1 (DOCX 18 kb)

References

  1. Abdi, H., Williams, L. J., & Valentin, D. (2013). Multiple factor analysis: Principal component analysis for multitable and multiblock data sets. Wiley Interdisciplinary Reviews: Computational Statistics, 5(2), 149–179.CrossRefGoogle Scholar
  2. Adams, J. (2005). Early citation counts correlation with accumulated impact. Scientometrics, 63(3), 567–581.CrossRefGoogle Scholar
  3. Aksnes, D. W. (2003). Characteristics of highly cited papers. Research Evaluation, 12(3), 159–170.CrossRefGoogle Scholar
  4. Amara, N., Landry, R., & Halilem, N. (2015). What can university administrators do to increase the publication and citation scores of their faculty members? Scientometrics, 103(2), 489–530.CrossRefGoogle Scholar
  5. Annalingam, A., Damayanthi, H., Jayawardena, R., & Ranasinghe, P. (2014). Determinants of the citation rate of medical research publications from a developing country. SpringerPlus, 3(1), 1–6.CrossRefGoogle Scholar
  6. Antoniou, G. A., Antoniou, S. A., Georgakarakos, E. I., Sfyroeras, G. S., & Georgiadis, G. S. (2015). Bibliometric analysis of factors predicting increased citations in the vascular and endovascular literature. Annals of Vascular Surgery, 29(2), 286–292.CrossRefGoogle Scholar
  7. Belussi, A., & Faloutsos, C. (1995). Estimating the selectivity of spatial queries using the ‘correlation’ fractal dimension. In Proceedings of the 21th international conference on very large data bases (pp. 299–310).Google Scholar
  8. Berchtold, S., Böhm, C., & Kriegel, H.-P. (1998). The pyramid-tree: Breaking the curse of dimensionality. In Proceedings of the ACM SIGMOD international conference on management of data (pp. 142–153).Google Scholar
  9. Biscaro, C., & Giupponi, C. (2014). Co-authorship and bibliographic coupling network effects on citations. PLoS ONE, 9(6), e99502.CrossRefGoogle Scholar
  10. Bjarnason, T., & Sigfusdottir, I. D. (2002). Nordic impact: Article productivity and citation patterns in sixteen Nordic Sociology departments. Acta Sociologica, 45(4), 253–267.CrossRefGoogle Scholar
  11. Bornmann, L. (2013). The problem of citation impact assessments for recent publication years in institutional evaluations. Journal of Informetrics, 7(3), 722–729.CrossRefGoogle Scholar
  12. Bornmann, L. (2014). Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics. Journal of Informetrics, 8(4), 895–903.CrossRefGoogle Scholar
  13. Bornmann, L., & Daniel, H. D. (2010). Citation speed as a measure to predict the attention an article receives: An investigation of the validity of editorial decisions at Angewandte Chemie International Edition. Journal of Informetrics, 4(1), 83–88.CrossRefGoogle Scholar
  14. Bornmann, L., Schier, H., Marx, W., & Daniel, H.-D. (2012). What factors determine citation counts of publications in chemistry besides their quality? Journal of Informetrics, 6(1), 11–18.CrossRefGoogle Scholar
  15. Bornmann, L., & Williams, R. (2013). How to calculate the practical significance of citation impact differences? An empirical example from evaluative institutional bibliometrics using adjusted predictions and marginal effects. Journal of Informetrics, 7(2), 562–574.CrossRefGoogle Scholar
  16. Borsuk, R. M., Budden, A. E., Leimu, R., Aarssen, L. W., & Lortie, C. J. (2009). The influence of author gender, national language and number of authors on citation rate in ecology. Open Ecology Journal, 2(1), 25–28.CrossRefGoogle Scholar
  17. Bosquet, C., & Combes, P. P. (2013). Are academics who publish more also more cited? Individual determinants of publication and citation records. Scientometrics, 97(3), 831–857.CrossRefGoogle Scholar
  18. Breiman, L. (2001). Random forests. Machine Learning, 45, 5–32.zbMATHCrossRefGoogle Scholar
  19. Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and regression trees. New York: Wadsworth.zbMATHGoogle Scholar
  20. Buela-Casal, G., & Zych, I. (2010). Analysis of the relationship between the number of citations and the quality evaluated by experts in psychology journals. Psicothema, 22(2), 270–276.Google Scholar
  21. Chakraborty, T., Kumar, S., Goyal, p. Ganguly, N. & Mukherjee, A. (2014). Towards a stratified learning approach to predict future citation counts. In Proceedings of the ACM/IEEE joint conference on digital libraries.Google Scholar
  22. Chen, C. M. (2012). Predictive effects of structural variation on citation counts. Journal of the American Society for Information Science and Technology, 63(3), 431–449.CrossRefGoogle Scholar
  23. Chi, P. S., & Glänzel, W. (2017). An empirical investigation of the associations among usage, scientific collaboration and citation impact. Scientometrics, 112(1), 403–412.CrossRefGoogle Scholar
  24. Chi, P. S., & Glänzel, W. (2018). Comparison of citation and usage indicators in research assessment in scientific disciplines and journals. Scientometrics, 116(1), 537–554.CrossRefGoogle Scholar
  25. Collet, F., Robertson, D. A., & Lup, D. (2014). When does brokerage matter? Citation impact of research teams in an emerging academic field. Strategic Organization, 12(3), 157–179.CrossRefGoogle Scholar
  26. Dalen, Van, & Henkens, H. P. K. (2005). Signals in science-On the importance of signaling in gaining attention in science. Scientometrics, 64(2), 209–233.CrossRefGoogle Scholar
  27. de Winter, J. (2015). The relationship between tweets, citations, and article views for PLOS ONE articles. Scientometrics, 102(2), 1773–1779.CrossRefGoogle Scholar
  28. Didegah, F., Bowman, T. D., & Holmberg, K. (2018). On the difference between citations and altmetrics: An investigation of factors driving altmetrics versus citations for Finnish articles. Journal of the Association for Information Science and Technology, 69(6), 832–843.CrossRefGoogle Scholar
  29. Didegah, F., & Thelwall, M. (2013). Determinants of research citation impact in nanoscience and nanotechnology. Journal of the American Society for Information Science and Technology, 64(5), 1055–1064.CrossRefGoogle Scholar
  30. Dorta-González, P., Dorta-González, M. I., Santos-Peñate, D. R., & Suárez-Vega, R. (2014). Journal topic citation potential and between-field comparisons: The topic normalized impact factor. Journal of Informetrics, 8(2), 406–418.CrossRefGoogle Scholar
  31. Dudani, S. A. (1976). The distance-weighted k-nearest neighbor rule. IEEE Transactions on System Man and Cybernetics, 6(4), 325–327.CrossRefGoogle Scholar
  32. Ebrahim, N. A., Salehi, H., Embi, M. A., Tanha, F. H., Gholizadeh, H., & Motahar, S. M. (2014). Visibility and citation impact. International Education Studies, 7(4), 120–125.CrossRefGoogle Scholar
  33. Eysenbach, G. (2011). Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact. Journal of Medical Internet Research, 13(4), e123.CrossRefGoogle Scholar
  34. Falagas, M. E., Zarkali, A., Karageorgopoulos, D. E., Bardakas, V., & Mavros, M. N. (2013). The impact of article length on the number of future citations: A bibliometric analysis of general medicine journals. PLoS ONE, 8(2), e49476.CrossRefGoogle Scholar
  35. Farshad, M., Sidler, C., & Gerber, C. (2013). Association of scientific and nonscientific factors to citation rates of articles of renowned orthopedic journals. European Orthopedics and Traumatology, 4(3), 125–130.CrossRefGoogle Scholar
  36. Fausto, S., Machado, F. A., Bento, L. F. J., Iamarino, A., Nahas, T. R., & Munger, D. S. (2012). Research blogging: indexing and registering the change in science 2.0. PLoS One, 7(12), e50109.CrossRefGoogle Scholar
  37. Frandsen, T. F., & Nicolaisen, J. (2013). The ripple effect: Citation chain reactions of a nobel prize. Journal of the American Society for Information Science and Technology, 64(3), 437–447.CrossRefGoogle Scholar
  38. Garner, J., Porter, A. L., & Newman, N. C. (2014). Distance and velocity measures: Using citations to determine breadth and speed of research impact. Scientometrics, 100(3), 687–703.CrossRefGoogle Scholar
  39. Glänzel, W. (2008). Seven myths in bibliometrics. About facts and fiction in quantitative science studies. In 4th International conference on webometrics, informetrics and scientometrics & 9th COLLNET meeting, Berlin, Germany.Google Scholar
  40. Glänzel, W., & Heeffer, S. (2014). Cross-national preferences and similarities in downloads and citations of scientific articles: a pilot study. In E. Noyons (Ed.), Proceedings of the STI conference 2014, Leiden (pp. 207–215).Google Scholar
  41. Glänzel, W., Rousseau, R., & Zhang, L. (2012). A visual representation of relative first-citation times. Journal of the American Society for Information Science and Technology, 63(7), 1420–1425.CrossRefGoogle Scholar
  42. Glänzel, W., & Schubert, A. (2003). A new classification scheme of science fields and subfields designed for scientometric evaluation purposes. Scientometrics, 56(3), 357–367.CrossRefGoogle Scholar
  43. Glänzel, W., & Thijs, B. (2004). Does co-authorship inflate the share of self-citations? Scientometrics, 61(3), 395–404.CrossRefGoogle Scholar
  44. Glänzel, W., Thijs, B., & Debackere, K. (2014). The application of citation-based performance classes to the disciplinary and multidisciplinary assessment in national comparision and institutional research assessment. Scientometrics, 101(2), 939–952.CrossRefGoogle Scholar
  45. Gonzalez-Alcaide, G., Calafat, A., Becona, E., Thijs, B., & Glänzel, W. (2016). Co-citation analysis of articles published in substance abuse journals: Intellectual structure and research fields (2001-2012). Journal of Studies on Alcohol and Drugs, 77(5), 710–722.CrossRefGoogle Scholar
  46. Guerrero-Bote, V. P., & Moya-Anegón, F. (2014). Relationship between downloads and citations at journal and paper levels, and the influence of language. Scientometrics, 101(2), 1043–1065.CrossRefGoogle Scholar
  47. Haslam, N., & Koval, P. (2010). Predicting long-term citation impact of articles in social and personality psychology. Psychological Reports, 106(3), 891–900.CrossRefGoogle Scholar
  48. Haustein, S., Larivière, V., Thelwall, M., Amyot, D., & Peters, I. (2014). Tweets vs. Mendeley readers: How do these two social media metrics differ? IT-Information Technology, 56(5), 207–215.CrossRefGoogle Scholar
  49. Haustein, S., Peters, I., Bar-Ilan, J., Priem, J., Hadas, S., & Terliesner, J. (2013). Coverage and adoption of altmetrics sources in the bibliometric community. In Proceeding of 14th international society of scientometrics and informatics conference (pp. 468–483).Google Scholar
  50. Herrmannova, D., Patton, R. M., Knoth, P., & Stahl, C. G. (2018). Do citations and readership identify seminal publications? Scientometrics, 115(1), 239–262.CrossRefGoogle Scholar
  51. Hilmer, C. E., & Lusk, J. L. (2009a). Determinants of citations to the agricultural and applied economics association journals. Review of Agricultural Economics, 31(4), 677–694.CrossRefGoogle Scholar
  52. Hilmer, C. E., & Lusk, J. L. (2009b). Determinants of citations to the agricultural and applied economics association journals. Reviews of Agricultural Economics, 31(4), 677–694.CrossRefGoogle Scholar
  53. Huang, H., Andrews, J., & Tang, J. (2012). Citation characterization and impact normalization in bioinformatics journals. Journal of the American Society for Information Science and Technology, 63(3), 490–497.CrossRefGoogle Scholar
  54. Huang, S., Chang, J., Leng, G., & Huang, Q. (2015). Integrated index for drought assessment based on variable fuzzy set theory: A case study in the Yellow River basin. Journal of Hydrology, 527, 608–618.CrossRefGoogle Scholar
  55. Hurley, L. A., Ogier, A. L., & Torvik, V. I. (2013). Deconstructing the collaborative impact: Article and author characteristics that influence citation count. Proceedings of the ASIST Annual Meeting, 50(1), 1–10.Google Scholar
  56. Ibáñez, A., Bielza, C., & Larrañaga, P. (2013). Relationship among research collaboration, number of documents and number of citations: A case study in Spanish computer science production in 2000-2009. Scientometrics, 95(2), 689–716.CrossRefGoogle Scholar
  57. Ingwersen, P., & Larsen, B. (2014). Influence of a performance indicator on Danish research production and citation impact 2000-12. Scientometrics, 101(2), 1325–1344.CrossRefGoogle Scholar
  58. Ingwersen, P., Larsen, B., Garcia-Zorita, J. C., Serrano-Lopez, A. E., & Sanz-Casado, E. (2014). Influence of proceedings papers on citation impact in seven sub-fields of sustainable energy research 2005-2011. Scientometrics, 101(2), 1273–1292.CrossRefGoogle Scholar
  59. Ke, S. W., Lin, W. C., Tsai, C. F., & Hu, Y. H. (2014). Citation impact analysis of research papers that appear in oral and poster sessions: A case study of three computer science conference. Online Information Review, 38(6), 738–745.CrossRefGoogle Scholar
  60. Kononenko, I. (1994). Estimating attributes: Analysis and extensions of RELIEF. In European conference on machine learning (pp. 171–182).Google Scholar
  61. Korn, F., Pagel, B.-U., & Faloutsos, C. (2001). On the ‘dimensionality curse’ and the ‘self-similarity blessing’. IEEE TKDE, 13, 96–111.Google Scholar
  62. Kousha, K., & Thelwall, M. (2017). Are Wikipedia citations important evidence of the impact of scholarly articles and books? Journal of the Association for Information Science and Technology, 68(3), 762–779.CrossRefGoogle Scholar
  63. Langley, P., Iba, W., & Thompson, K. (1992). An analysis of Bayesian classifers. In Proceedings of the 10th national conference on artificial intelligence (pp. 223–228).Google Scholar
  64. Lee, S. Y., Lee, S., & Jun, S. H. (2010). Author and article characteristics, journal quality and citation in economic research. Applied Economics Letters, 17(17), 1697–1701.CrossRefGoogle Scholar
  65. Leimu, R., & Koricheva, J. (2005). What determines the citation frequency of ecological papers? Trends in Ecology & Evolution, 20(1), 28–32.CrossRefGoogle Scholar
  66. Li, X., Thelwall, M., & Giustini, D. (2012). Validating online reference managers for scholarly impact measurement. Scientometrics, 91(2), 461–471.CrossRefGoogle Scholar
  67. Lira, R. P. C., Vieira, R. M. C., Goncalves, F. A., Ferreira, M. C. A., Maziero, D., & Arieta, C. E. L. (2013). Influence of English language in the number of citations of articles published in Brazilian journals of Ophthalmology. Arquivos Brasileiros de Oftalmologia, 76(1), 26–28.CrossRefGoogle Scholar
  68. Marashi, S. A., Hosseini-Nami, S., Alishah, K., Hadi, M., Karimi, A., Hosseinian, S., et al. (2013). Impact of wikipeida on citation trends. Excli Journal, 12, 15–19.Google Scholar
  69. McCabe, M. J., & Snyder, C. M. (2015). Does online availability increase citations? Theory and evidence from a panel of economics and business journals. Review of Economics and Statistics, 97(1), 144–165.CrossRefGoogle Scholar
  70. Miettunen, J., & Nieminen, P. (2003). The effect of statistical methods and study reporting characteristics on the number of citations: A study of four general psychiatric journals. Scientometrics, 57(3), 377–388.CrossRefGoogle Scholar
  71. Naraei, P. & Sadeghian, A. (2017). A PCA based feature reduction in intracranial hypertension analysis. In IEEE international conference on 30th Canadian conference on electrical and computer engineering (pp. 1–6).Google Scholar
  72. Neylon, C., & Wu, S. (2009). Article-level metrics and the evolution of scientific impact. PLoS Biology, 7(11), e1000242.CrossRefGoogle Scholar
  73. Nomaler, T., Frenken, K., & Heimeriks, G. (2013). Do more distant collaborations have more citation impact? Journal of Informetrics, 7(4), 966–971.CrossRefGoogle Scholar
  74. Onodera, N., & Yoshikane, F. (2015). Factors affecting citation rates of research articles. Journal of the Association for Information Science and Technology, 66(4), 739–764.CrossRefGoogle Scholar
  75. Onyancha, O. B., & Maluleka, J. R. (2011). Knowledge production through collaborative research in sub-Saharan Africa: How much do countries contribute to each other’s knowledge output and citation impact? Scientometrics, 87(2), 315–336.CrossRefGoogle Scholar
  76. Ortega, J. (2016). To be or not to be on Twitter, and its relationship with the tweeting and citation of research papers. Scientometrics, 109(2), 1353–1364.CrossRefGoogle Scholar
  77. Padial, A. A., Nabout, J. C., Siqueira, T., Bini, L. M., & Diniz-Filho, J. A. F. (2010). Weak evidence for determinants of citation frequency in ecological articles. Scientometrics, 85(1), 1–12.CrossRefGoogle Scholar
  78. Pagel, P. S., & Hudetz, J. A. (2011). Scholarly productivity of United States academic cardiothoracic anesthesiologists: Influence of fellowship accreditation and transesophageal echocardiographic credentials on h-index and other citation bibliometrics. Journal of Cardiothoracic and Vascular Anesthesia, 25(5), 761–765.CrossRefGoogle Scholar
  79. Pagel, B.-U., Korn, F. & Faloutsos, C. (2000). Deflating the dimensionality curse using multiple fractal dimensions. In 16th ICDE (pp. 589–598).Google Scholar
  80. Patterson, M. S., & Harris, S. (2009). The relationship between reviewers’ quality-scores and number of citations for papers published in the journal physics in medicine and biology from 2003-2005. Scientometrics, 80(2), 343–349.CrossRefGoogle Scholar
  81. Peoples, B., Midway, S., Sackett, D., Lynch, A., & Cooney, P. B. (2016). Twitter predicts citation rates of ecological research. PLoS ONE, 11, e0166570.CrossRefGoogle Scholar
  82. Piwowar, H., & Priem, J. (2013). The power of altmetrics on a CV. Bulletin of the Association for Information Science and Technology, 39(4), 10–13.CrossRefGoogle Scholar
  83. Priem, J., & Hemminger, B. M. (2010). Scientometrics 2.0: Toward new metrics of scholarly impact on the social Web. First Monday, 15(7). Retrieved from https://journals.uic.edu/ojs/index.php/fm/article/view/2874/2570.
  84. Priem, J., Parra, C., Piwowar, H., Groth, P., & Waagmeester, A. (2012). Uncovering impacts: a case study in using altmetrics tools. In Second international conference on the future of scholarly communication and scientific publishing. Heraklion, Greece. http://jasonpriem.org/self-archived/altmetrics/sepublica/cameraready.pdf. Accessed 19 Mar 2013.
  85. Puuska, H. M., Muhonen, R., & Leino, Y. (2014). International and domestic co-publishing and their citation impact in different disciplines. Scientometrics, 98(2), 823–839.CrossRefGoogle Scholar
  86. Ravenscroft, J., Liakata, M., Clare, A., & Duma, D. (2017). Measuring scientific impact beyond academia: an assessment of existing impact metrics and proposed improvements. PLoS ONE, 12, e0173152.CrossRefGoogle Scholar
  87. Rees, T., Ayling-Rouse, K., & Smith, S. (2012). Accesses versus citations: Why you need to measure both to assess publication impact. Current Medical Research and Opinion, 28, S9–S10.CrossRefGoogle Scholar
  88. Ringelhan, S., Wollersheim, J., & Welpe, I. (2015). I like, I cite? Do facebook likes predict the impact of scientific work? PLoS ONE, 10, e0134389.CrossRefGoogle Scholar
  89. Royle, P., Kandala, N. B., Barnard, K., & Waugh, N. (2013). Bibliometrics of systematic reviews: Analysis of citation rates and journal impact factors. Systematic reviews, 2, 74.CrossRefGoogle Scholar
  90. Sangwal, K. (2012). On the relationship between citations of publication output and Hirsch index h of authors: Conceptualization of tapered Hirsch index h T, circular citation area radius R and citation acceleration a. Scientometrics, 93(3), 987–1004.CrossRefGoogle Scholar
  91. Schilling, M. A., & Green, E. (2011). Recombinant search and breakthrough idea generation: An analysis of high impact papers in the social sciences. Research Policy, 40(10), 1321–1331.CrossRefGoogle Scholar
  92. Shu, F., Lou, W., & Haustein, S. (2018). Can Twitter increase the visibility of Chinese publications? Scientometrics, 116(1), 505–519.CrossRefGoogle Scholar
  93. Sin, S. C. J. (2011). International coauthorship and citation impact: A bibliometric study of six LIS journals, 1980-2008. Journal of the American Society for Information Science and Technology, 62(9), 1770–1783.CrossRefGoogle Scholar
  94. Stremersch, S., Camacho, N., Vanneste, S., & Verniers, I. (2015). Unraveling scientific impact: Citation types in marketing journals. International Journal of Research in Marketing, 32(1), 64–77.CrossRefGoogle Scholar
  95. Stremersch, S., Verniers, I., & Verhoef, P. C. (2007). The quest for citations: Drivers of article impact. Journal of Marketing, 71(3), 171–193.CrossRefGoogle Scholar
  96. Syamili, C., & Rekha, R. V. (2017). Do altmetric correlate with citation? A study based on PLOS ONE journal. Journal of Scientometrics and Information Management, 11(1), 103–117.Google Scholar
  97. Tahamtan, I., Afshar, A. S., & Ahamdzadeh, K. (2016). Factors affecting number of citations: A comprehensive review of the literature. Scientometrics, 107(3), 1195–1225.CrossRefGoogle Scholar
  98. Tang, X., Wang, L., & Kishore, R. (2014). Why do is scholars cite other scholars? An empirical analysis of the direct and moderating effects of cooperation and competition among is scholars on individual citation behavior C3. In 35th International conference on information systems (ICIS 2014).Google Scholar
  99. Taylor, M. (2013). Exploring the boundaries: how altmetrics can expand our vision of scholarly communication and social impact. Information Standards Quarterly, 25(2), 27–32.CrossRefGoogle Scholar
  100. Thelwall, M. (2018). Early Mendeley readers correlate with later citation counts. Scientometrics, 115(3), 1231–1240.CrossRefGoogle Scholar
  101. Thelwall, M., Haustein, S., Larivière, V., & Sugimoto, C. (2013). Do altmetrics work? Twitter and ten other candidates. PLoS ONE, 8(5), e64841.CrossRefGoogle Scholar
  102. Thelwall, M., & Wilson, P. (2016). Mendeley readership altmetrics for medical articles: An analysis of 45 fields. Journal of the Association for Information Science and Technology, 67(8), 1962–1972.CrossRefGoogle Scholar
  103. Traina, C., Traina, A., Wu, L., & Faloutsos, C. (2000). Fast feature selection using fractal dimension. In Proceeding 15th Brazilian symposium on database (SBBD) (pp. 158–171).Google Scholar
  104. Van Der Pol, C. B., McInnes, M. D. F., Petrcich, W., Tunis, A. S., & Hanna, R. (2015). Is quality and completeness of reporting of systematic reviews and meta-analyses published in high impact radiology journals associated with citation rates? PLoS ONE, 10(3), e011892.Google Scholar
  105. van Eck, N. J., Waltman, L., van Raan, A. F. J., Klautz, R. J. M., & Peul, W. C. (2013). Citation analysis may severely underestimate the impact of clinical research as compared to basic research. PLoS ONE, 8(4), e62395.CrossRefGoogle Scholar
  106. Van Wesel, M., Wyatt, S., & ten Haaf, J. (2014). What a difference a colon makes: How superficial factors influence subsequent citation. Scientometrics, 98(3), 1601–1615.CrossRefGoogle Scholar
  107. Vanclay, J. K. (2013). Factors affecting citation rates in environmental science. Journal of Informetrics, 7(2), 265–271.CrossRefGoogle Scholar
  108. Vieira, E. S., & Gomes, J. A. N. F. (2010). Citations to scientific articles: Its distribution and dependence on the article features. Journal of Informetrics, 4(1), 1–13.CrossRefGoogle Scholar
  109. Walters, G. D. (2006). Predicting subsequent citations to article published in twelve crime-psychology journals: Author impact versus journal impact. Scientometrics, 69(3), 499–510.CrossRefGoogle Scholar
  110. Waltman, L., & Costas, R. (2014). F1000 recommendations as a potential new data source for research evaluation: A comparison with citations. Journal of the Association for Information Science and Technology, 65(3), 433–445.CrossRefGoogle Scholar
  111. Wang, X., Liu, C., Fang, Z., & Mao, W. (2014). From attention to citation, what and how does altmetrics work? http://arxiv.org/abs/1409.4269
  112. Wang, J., Thijs, B., & Glänzel, W. (2015a). Interdisciplinarity and impact: Distinct effects of variety, balance, and disparity. PLoS ONE, 10(5), e0127298.CrossRefGoogle Scholar
  113. Wang, L., Thijs, B., & Glänzel, W. (2015b). Characteristics of international collaboration in sport sciences publications and its influence on citation impact. Scientometrics, 105(2), 843–862.CrossRefGoogle Scholar
  114. Wang, M., Yu, G., An, S., & Yu, D. (2012a). Discovery of factors influencing citation impact based on a soft fuzzy rough set model. Scientometrics, 93(3), 635–644.CrossRefGoogle Scholar
  115. Wang, M., Yu, G., Xu, J., He, H., Yu, D., & An, S. (2012b). Development a case-based classifier for predicting highly cited papers. Journal of Informetrics, 6(4), 586–599.CrossRefGoogle Scholar
  116. Willis, D. L., Bahler, C. D., Neuberger, M. M., & Dahm, P. (2011). Predictors of citations in the urological literature. BJU International, 107(12), 1876–1880.CrossRefGoogle Scholar
  117. Xu, J. L., Xu, B. W., Zhang, W. F., & Cui, Z. F. (2008). Principal component analysis based feature selection for clustering. In 2008 international conference on machine learning and cybernetics (Vol. 1, pp. 460–465).Google Scholar
  118. Yu, T., & Yu, G. (2014). Features of scientific papers and the relationships with their citation impact. Malaysian Journal of Library and Information Science, 19(1), 37–50.Google Scholar
  119. Yu, T., Yu, G., Li, P. Y., & Wang, L. (2014). Citation impact prediction for scientific papers using stepwise regression analysis. Scientometrics, 101(2), 1233–1252.CrossRefGoogle Scholar
  120. Yuan, S. B., & Hua, W. N. (2011). Scholarly impact measurements of LIS open access journals: Based on citations and links. Electronic Library, 29(5), 682–697.MathSciNetCrossRefGoogle Scholar
  121. Yue, W. P., & Wilson, C. S. (2004). Measuring the citation impact of research journals in clinical neurology: A structural equation modelling analysis. Scientometrics, 60(3), 317–332.CrossRefGoogle Scholar
  122. Zahedi, Z., Costas, R. & Wouters, P. (2013). How well developed are Altmerics? Cross-disciplinary analysis of the presence of ‘alternative metrics’ in scientific publications. In 14th International society of scientometrics and informatics conference (pp. 876–884).Google Scholar

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