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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)

Abstract

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.

Keywords

Concept link Virtual reality Social media Text mining Twitter 

Notes

Acknowledgements

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

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

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

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