How video articles are cited, the case of JoVE: Journal of Visualized Experiments

Abstract

Journal of Visualized Experiments (JoVE) is a peer-reviewed journal that publishes video articles. In order to find out about the impact of video articles and how they are used in other journal articles, a random sample of 500 articles that cited at least one JoVE article was drawn and citation content analysis was conducted to find out about reasons for citation, frequency of citation mentions, location of citation and any relation between in-text citation characteristics and times cited. The results showed that JoVE articles are mostly cited for methodological reasons (72.4%) and in method sections of articles (53.2%). The context of 44.1% of citation mentions included phrases such as ‘as previously described’. More than a third (38.8%) of citations to JoVE articles were self-citations. JoVE articles that were self-cited were more likely to have a larger number of citation mentions, be cited for different reasons and in different sections of citing articles. They were also more likely to have more authors. The majority of the articles (75.6%) were mentioned only once in the citing articles. The median impact factor (MIF) of the journals of citing articles was higher than MIF of any Web of Science subject category, indicating that the citing articles were mostly from journals with relatively high impact factors. Overall, JoVE articles play an important role in transparency and transfer of methodologies and processes in research.

This is a preview of subscription content, access via your institution.

Fig. 1

Notes

  1. 1.

    https://clarivate.com/blog/science-research-connect/rising-stars-essential-science-indicators/.

References

  1. Aksnes, D. W. (2003). A macro study of self-citation. Scientometrics, 56(2), 235–246. https://doi.org/10.1023/A:1021919228368.

    Article  Google Scholar 

  2. An, J., Kim, N., Kan, M. Y., Chandrasekaran, M. K., & Song, M. (2017). Exploring characteristics of highly cited authors according to citation location and content. Journal of the Association for Information Science and Technology, 68(8), 1975–1988. https://doi.org/10.1002/asi.23834.

    Article  Google Scholar 

  3. Bertin, M., Atanassova, I., Gingras, Y., & Larivière, V. (2016). The invariant distribution of references in scientific articles. Journal of the Association for Information Science and Technology, 67(1), 164–177. https://doi.org/10.1002/asi.23367.

    Article  Google Scholar 

  4. Blagosklonny, M. V. (2018). Librarians against scientists: Oncotarget’s lesson. Oncotarget, 9(5), 5115–5116. https://doi.org/10.18632/oncotarget.24272.

    Article  Google Scholar 

  5. Bonzi, S., & Snyder, H. (1991). Motivations for citation: A comparison of self citation and citation to others. Scientometrics, 21(2), 245–254. https://doi.org/10.1007/BF02017571.

    Article  Google Scholar 

  6. Bornmann, L., & Daniel, H. (2008). What do citation counts measure? A review of studies on citing behavior. Journal of Documentation, 64(1), 45–80. https://doi.org/10.1108/00220410810844150.

    Article  Google Scholar 

  7. Bornmann, L., Mutz, R., Neuhaus, C., & Daniel, H. D. (2008). Citation counts for research evaluation: Standards of good practice for analyzing bibliometric data and presenting and interpreting results. Ethics in Science and Environmental Politics, 8(1), 93–102. https://doi.org/10.3354/esep00084.

    Article  Google Scholar 

  8. Boyack, K. W., van Eck, N. J., Colavizza, G., & Waltman, L. (2018). Characterizing in-text citations in scientific articles: A large-scale analysis. Journal of Informetrics, 12(1), 59–73. https://doi.org/10.1016/j.joi.2017.11.005.

    Article  Google Scholar 

  9. Case, D. O., & Higgins, G. M. (2000). How can we investigate citation behavior? A study of reasons for citing literature in communication. Journal of the Association for Information Science and Technology, 51(7), 635–645. https://doi.org/10.1002/(SICI)1097-4571(2000)51:7%3c635:AID-ASI6%3e3.0.CO;2-H.

    Article  Google Scholar 

  10. Cayar, C. (2011). The YouTube effect: How YouTube has provided new ways to consume, create, and share music. International Journal of Education & the Arts, 12(6). http://www.ijea.org/v12n6/. Accessed 15 Aug 2018.

  11. Ding, Y., Liu, X., Guo, C., & Cronin, B. (2013). The distribution of references across texts: Some implications for citation analysis. Journal of Informetrics, 7(3), 583–592. https://doi.org/10.1016/j.joi.2013.03.003.

    Article  Google Scholar 

  12. Ding, Y., Zhang, G., Chambers, T., Song, M., Wang, X., & Zhai, C. (2014). Content-based citation analysis: The next generation of citation analysis. Journal of the Association for Information Science and Technology, 65(9), 1820–1833. https://doi.org/10.1002/asi.23256.

    Article  Google Scholar 

  13. Erviti, M. D. C., & Stengler, E. (2016). Online science videos: An exploratory study with major professional content providers in the United Kingdom. Journal of Science Communication, 15(6), A06. https://jcom.sissa.it/archive/15/06/JCOM_1506_2016_A06. Accessed 15 Aug 2018.

  14. Fowler, J., & Aksnes, D. (2007). Does self-citation pay? Scientometrics, 72(3), 427–437. https://doi.org/10.1007/s11192-007-1777-2.

    Article  Google Scholar 

  15. Gilbert, G. N. (1977). Referencing as persuasion. Social Studies of Science, 7(1), 113–122.

    Article  Google Scholar 

  16. Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172. https://doi.org/10.1016/j.joi.2008.02.001.

    Article  Google Scholar 

  17. Hanney, S., Frame, I., Grant, J., Buxton, M., Young, T., & Lewison, G. (2005). Using categorisations of citations when assessing the outcomes from health research. Scientometrics, 65(3), 357–379. https://doi.org/10.1007/s11192-005-0279-y.

    Article  Google Scholar 

  18. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569–16572. https://doi.org/10.1073/pnas.0507655102.

    Article  MATH  Google Scholar 

  19. Hu, Z., Chen, C., & Liu, Z. (2013). Where are citations located in the body of scientific articles? A study of the distributions of citation locations. Journal of Informetrics, 7(4), 887–896. https://doi.org/10.1016/j.joi.2013.08.005.

    Article  Google Scholar 

  20. Hu, Z., Chen, C., & Liu, Z. (2015). The recurrence of citations within a scientific article. In 15th International Society of Scientometrics and Informetrics Conference (pp. 221–229).

  21. Hu, Z., Lin, G., Sun, T., & Hou, H. (2017). Understanding multiply mentioned references. Journal of Informetrics, 11(4), 948–958. https://doi.org/10.1016/j.joi.2017.08.004.

    Article  Google Scholar 

  22. Jones, T., & Cuthrell, K. (2011). YouTube: Educational potentials and pitfalls. Computers in the Schools, 28(1), 75–85. https://doi.org/10.1080/07380569.2011.553149.

    Article  Google Scholar 

  23. Kousha, K., Thelwall, M., & Abdoli, M. (2012). The role of online videos in research communication: A content analysis of YouTube videos cited in academic publications. Journal of the Association for Information Science and Technology, 63(9), 1710–1727. https://doi.org/10.1002/asi.22717.

    Article  Google Scholar 

  24. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310.

    Article  MATH  Google Scholar 

  25. Lu, C., Ding, Y., & Zhang, C. (2017). Understanding the impact change of a highly cited article: A content-based citation analysis. Scientometrics, 112(2), 927–945. https://doi.org/10.1007/s11192-017-2398-7.

    Article  Google Scholar 

  26. McCain, K., & Turner, K. (1989). Citation context analysis and aging patterns of journal articles in molecular genetics. Scientometrics, 17(1–2), 127–163. https://doi.org/10.1007/BF02017729.

    Article  Google Scholar 

  27. Merton, R. K. (1973). The sociology of science: Theoretical and empirical investigations. Chicago, IL: University of Chicago Press.

    Google Scholar 

  28. Moed, H. F., & Van Der Velde, J. G. M. (1993). Bibliometric profiles of academic chemistry research in the Netherlands, Centre for Science and Technology Studies. Report CWTS-93-08, Leiden.

  29. Orduna-Malea, E., Thelwall, M., & Kousha, K. (2017). Web citations in patents: Evidence of technological impact? Journal of the Association for Information Science and Technology, 68(8), 1967–1974. https://doi.org/10.1002/asi.23821.

    Article  Google Scholar 

  30. Pak, C., Yu, G., & Wang, W. (2018). A study on the citation situation within the citing paper: Citation distribution of references according to mention frequency. Scientometrics, 114(3), 905–918. https://doi.org/10.1007/s11192-017-2627-0.

    Article  Google Scholar 

  31. Pasquali, M. (2007). Video in science: Protocol videos: The implications for research and society. EMBO Reports, 8(8), 712–716. https://doi.org/10.1038/sj.embor.7401037.

    Article  Google Scholar 

  32. Seeber, M., Cattaneo, M., Meoli, M., & Malighetti, P. (2018). Self-citations as strategic response to the use of metrics for career decisions. Research Policy. https://doi.org/10.1016/j.respol.2017.12.004. (in press).

    Article  Google Scholar 

  33. Sugimoto, C. R., & Thelwall, M. (2013). Scholars on soap boxes: Science communication and dissemination in TED videos. Journal of the Association for Information Science and Technology, 64(4), 663–674. https://doi.org/10.1002/asi.22764.

    Article  Google Scholar 

  34. Sugimoto, C. R., Thelwall, M., Larivière, V., Tsou, A., Mongeon, P., & Macaluso, B. (2013). Scientists popularizing science: Characteristics and impact of TED talk presenters. PLoS ONE, 8(4), e62403. https://doi.org/10.1371/journal.pone.0062403.

    Article  Google Scholar 

  35. Thelwall, M., & Wilson, P. (2016). Does research with statistics have more impact? The citation rank advantage of structural equation modeling. Journal of the Association for Information Science and Technology, 67, 1233–1244. https://doi.org/10.1002/asi.23474.

    Article  Google Scholar 

  36. Thornley, C., Watkinson, A., Nicholas, D., Volentine, R., Jamali, H. R., Herman, E., Allard, S., Levine, K. J., & Tenopir, C. (2015). The role of tust and authority in the citation behaviour of researchers. Information Research, 20(3), paper 677. http://InformationR.net/ir/20-3/paper677.html. Accessed 15 Aug 2018.

  37. Tohidinasab, F., & Jamali, H. R. (2013). Why and where Wikipedia is cited in journal articles? Journal of Scientometric Research, 2(3), 231–238. https://doi.org/10.4103/2320-0057.135415.

    Article  Google Scholar 

  38. Tsou, A., Thelwall, M., Mongeon, P., & Sugimoto, C. R. (2014). A community of curious souls: An analysis of commenting behavior on TED talks videos. PLoS ONE, 9(4), e93609. https://doi.org/10.1371/journal.pone.0093609.

    Article  Google Scholar 

  39. Van Leeuwen, T. N., Rinia, E. J., & Van Raan, A. F. J. (1996). Bibliometric profiles of academic physics research in the Netherlands. Centre for Science and Technology Studies. Report CWTS 96-09, Leiden.

  40. Vinkler, P. (1987). A quasi-quantitative citation model. Scientometrics, 12(1–2), 47–72. https://doi.org/10.1007/BF02016689.

    Article  Google Scholar 

  41. Voos, H., & Dagaev, K. S. (1976). Are all citations equal? Or, did we op. cit. your idem? Journal of Academic Librarianship, 1(6), 19–21.

    Google Scholar 

  42. Wan, X., & Liu, F. (2014). WL-index: Leveraging citation mention number to quantify an individual’s scientific impact. Journal of the Association for Information Science and Technology, 65(12), 2509–2517. https://doi.org/10.1002/asi.23151.

    Article  Google Scholar 

  43. White, M. D., & Wang, P. (1997). A qualitative study of citing behavior: Contributions, criteria, and metalevel documentation concerns. The Library Quarterly, 67(2), 122–154.

    Article  Google Scholar 

  44. Xu, S., Yu, H., Hemminger, B. M., & Dong, X. (2017). Communicating scientific video articles on Twitter: An initial exploration of JoVE publications. In Proceeding of 16th international conference on scientometrics and informetrics, 16–20 October 2017 (pp. 442–447). Wuhan: Wuhan University.

  45. Zhang, G., Ding, Y., & Milojević, S. (2013). Citation content analysis (CCA): A framework for syntactic and semantic analysis of citation content. Journal of the Association for Information Science and Technology, 64(7), 1490–1503. https://doi.org/10.1002/asi.22850.

    Article  Google Scholar 

  46. Zhao, D., Cappello, A., & Johnston, L. (2017). Functions of uni- and multi-citations: Implications for weighted citation analysis. Journal of Data and Information Science, 2(1), 51–69. https://doi.org/10.1515/jdis-2017-0003.

    Article  Google Scholar 

  47. Zhu, Y. (2017). Academics’ active and passive use of YouTube for research and leisure. In A. Esposito (Ed.), Research 2.0 and the impact of digital technologies on scholarly inquiry (pp. 188–210). Hershey, PA: IGI Global. https://doi.org/10.4018/978-1-5225-0830-4.ch010.

    Chapter  Google Scholar 

  48. Zhu, X., Turney, P., Lemire, D., & Vellino, A. (2015). Measuring academic influence: Not all citations are equal. Journal of the Association for Information Science and Technology, 66(2), 408–427. https://doi.org/10.1002/asi.23179.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Hamid R. Jamali.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jamali, H.R., Nabavi, M. & Asadi, S. How video articles are cited, the case of JoVE: Journal of Visualized Experiments. Scientometrics 117, 1821–1839 (2018). https://doi.org/10.1007/s11192-018-2957-6

Download citation

Keywords

  • JoVE
  • Journal of Visualized Experiments
  • Citation analysis
  • Citation motivation
  • Citation mentions
  • Citation content analysis
  • Research impact