Temporal Trend Analysis on Virtual Reality Using Social Media Mining

  • Chen-wen ShenEmail author
  • Jung-tsung Ho
  • Hung-wen Ma
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


Many studies have discussed the widespread use of virtual reality (VR). However, few studies have investigated VR from the perspective of social media, even though social media has changed how people communicate and emerged as an essential marketing channel. An approach of two-layer hierarchical concept decomposition structure was proposed to investigate the temporal trend of VR development from the perspective of the public. Accordingly, Twitter posts related to VR in 2015 and 2016 were crawled and analyzed by our proposed approach. The mining results determined that public focus shifted from VR headsets in 2015 to content in 2016. This suggests that VR devices are perceived as having gradually developed and that the next challenge and business opportunity is VR content and applications. In the era of big data and artificial intelligence, our concept decomposition approach contributes to the content analysis of acquiring insight from massive user-generated content, which extracts temporal trends in a holistic view and individual insights on a detailed scale.


Concept link Virtual reality Social media Text mining Twitter 



This research was supported by the Ministry of Science and Technology, Taiwan, under contract number MOST 107-2410-H-008-042.


  1. 1.
    IDC.: Worldwide shipments of augmented reality and virtual reality headsets expected to grow at 58% CAGR with low-cost smartphone VR devices being short-term catalyst, according to IDC 2017 [cited 2018 June 05]; Available from:
  2. 2.
    Kreiss, D.: Seizing the moment: the presidential campaigns’ use of Twitter during the 2012 electoral cycle. New Med. Soc. 18(8), 1473–1490 (2016)CrossRefGoogle Scholar
  3. 3.
    Hays, S., Page, S.J., Buhalis, D.: Social media as a destination marketing tool: its use by national tourism organisations. Curr. Issues Tourism 16(3), 211–239 (2013)CrossRefGoogle Scholar
  4. 4.
    Neubaum, G., Krämer, N.C.: Opinion climates in social media: blending mass and interpersonal communication. Hum. Commun. Res. 43(4), 464–476 (2017)CrossRefGoogle Scholar
  5. 5.
    Turner, C.J., et al.: Discrete event simulation and virtual reality use in industry: new opportunities and future trends. IEEE Trans. Hum.-Mach. Syst. 46(6), 882–894 (2016)CrossRefGoogle Scholar
  6. 6.
    Bovet, S., et al.: The critical role of self-contact for embodiment in virtual reality. IEEE Trans. Vis. Comput. Graph. 24(4), 1428–1436 (2018)CrossRefGoogle Scholar
  7. 7.
    Shen, C.-W., et al.: Behavioural intentions of using virtual reality in learning: perspectives of acceptance of information technology and learning style. Virtual Reality (2018)Google Scholar
  8. 8.
    Zhao, X., et al.: Analysis of mental workload in online shopping: are augmented and virtual reality consistent? Front. Psychol. 8, 71 (2017)CrossRefGoogle Scholar
  9. 9.
    Gerber, S.M., et al.: Visuo-acoustic stimulation that helps you to relax: a virtual reality setup for patients in the intensive care unit. Sci. Rep. 7(1), 13328 (2017)CrossRefGoogle Scholar
  10. 10.
    Vince, J.: Introduction to virtual reality. Springer Science & Business Media (2004)Google Scholar
  11. 11.
    Burdea, G.C., Coiffet, P.: Virtual Reality Technology, vol. 1. John Wiley & Sons (2003)Google Scholar
  12. 12.
    Burdea, G.C.: Keynote address: haptics feedback for virtual reality. In: Proceedings of International Workshop on Virtual Prototyping. Laval, France (1999)Google Scholar
  13. 13.
    Jonassen, D.H.: Transforming learning with technology: beyond modernism and post-modernism or whoever controls the technology creates the reality. Educ. Technol. 40(2), 21–25 (2000)Google Scholar
  14. 14.
    Huang, H.-M., Rauch, U., Liaw, S.-S.: Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach. Comput. Educ. 55(3), 1171–1182 (2010)CrossRefGoogle Scholar
  15. 15.
    Huang, H.-M., Liaw, S.-S., Lai, C.-M.: Exploring learner acceptance of the use of virtual reality in medical education: a case study of desktop and projection-based display systems. Interact. Learn. Environ. 24(1), 3–19 (2016)CrossRefGoogle Scholar
  16. 16.
    de Strulle, A.: Differentiation of the causal characteristics and influences of virtual reality and the effects on learning at a science exhibit. University of San Diego (2004)Google Scholar
  17. 17.
    Van Wyk, E., De Villiers, R.: Virtual reality training applications for the mining industry. In: Proceedings of the 6th International Conference on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa. ACM (2009)Google Scholar
  18. 18.
    Lu, J., et al.: Virtual learning environment for medical education based on VRML and VTK. Comput. Graph. 29(2), 283–288 (2005)CrossRefGoogle Scholar
  19. 19.
    Higgins, G.A., et al.: Teleos™: development of a software toolkit for authoring virtual medical environments. Presence: Teleoperators and Virtual Environ. 6(2), 241–252 (1997)CrossRefGoogle Scholar
  20. 20.
    Temkin, B., et al.: Web-based three-dimensional virtual body structures: W3D-VBS. J. Am. Med. Inform. Assoc. 9(5), 425–436 (2002)CrossRefGoogle Scholar
  21. 21.
    Mikropoulos, T.A., Natsis, A.: Educational virtual environments: a ten-year review of empirical research (1999–2009). Comput. Educ. 56(3), 769–780 (2011)CrossRefGoogle Scholar
  22. 22.
    Dickey, M.D.: Brave new (interactive) worlds: a review of the design affordances and constraints of two 3D virtual worlds as interactive learning environments. Interact. Learn. Environ. 13(1–2), 121–137 (2005)CrossRefGoogle Scholar
  23. 23.
    Merchant, G.: Literacy in virtual worlds. J. Res. Reading 32(1), 38–56 (2009)CrossRefGoogle Scholar
  24. 24.
    Pontonnier, C., et al.: Designing and evaluating a workstation in real and virtual environment: toward virtual reality based ergonomic design sessions. J. Multimodal User Interfaces 8(2), 199–208 (2014)CrossRefGoogle Scholar
  25. 25.
    Chakraborty, G., Pagolu, M., Garla, S.: Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. 2014: SAS InstituteGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Business AdministrationNational Central UniversityJhongli District, Taoyuan CityTaiwan, Republic of China

Personalised recommendations