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Author:

Wu, Feifei (Wu, Feifei.) | Tong, Yiming (Tong, Yiming.) | Huang, Lucheng (Huang, Lucheng.) (Scholars:黄鲁成) | Miao, Hong (Miao, Hong.) | Li, Xin (Li, Xin.)

Indexed by:

EI Scopus

Abstract:

Through determining the choice of the social media(WeChat) adhere to the criteria of the WCI, the WeChat Official Accounts which contain professional technical background and knowledge transmission target can be filtered as the research objects in the paper. The purpose of this paper is to finish the topic analysis of the information in the WeChat Official Accounts via the method of text mining, along with the support of regarding the push notifications in the WeChat Official Accounts as the data set. Combined with the judgement of social cognition based on diverse topics, the conclusion of application prospect analysis of technology will be verified with the trial of the topic model and sentiment analysis. Finally, a case study of application prospect analysis of graphene Technology serves as the role of the empirical research in this paper. © 2018 Portland International Conference on Management of Engineering and Technology, Inc. (PICMET).

Keyword:

Economics Sentiment analysis Text mining

Author Community:

  • [ 1 ] [Wu, Feifei]School of Economics and Management, Beijing University of Technology, Beijing, China
  • [ 2 ] [Wu, Feifei]Research Base of Beijing Modern Manufacturing Development, Beijing, China
  • [ 3 ] [Tong, Yiming]School of Economics and Management, Beijing University of Technology, Beijing, China
  • [ 4 ] [Huang, Lucheng]School of Economics and Management, Beijing University of Technology, Beijing, China
  • [ 5 ] [Huang, Lucheng]Research Base of Beijing Modern Manufacturing Development, Beijing, China
  • [ 6 ] [Miao, Hong]School of Economics and Management, Beijing University of Technology, Beijing, China
  • [ 7 ] [Li, Xin]School of Economics and Management, Beijing University of Technology, Beijing, China
  • [ 8 ] [Li, Xin]Research Base of Beijing Modern Manufacturing Development, Beijing, China

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Source :

Year: 2018

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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