Social evaluation of innovative drugs: A method based on big data analytics

Genghui Dai1, Xinshuang Fu2, Weihui Dai3 and Shengqi Lu4

  1. School of Marine Sciences, Sun Yat-Sen University
    Guangzhou 200433, China
  2. School of Management, Shanghai University
    Shanghai 200444, China
  3. School of Management, Fudan University
    Shanghai 200433, China
  4. School of Information Management and Engineering, Shanghai University of Finance and Economics
    Shanghai 200433, China


The evaluation of drugs is a professional and time consuming process which involves a series of clinical trials and evidence-based verifications. However, an innovative drug may still suffer from unpredictable risks after coming into market due to the complex circumstances in practical utilization. Owing to the popularization of information networks and social media, big data analytics exhibits a new perspective of social evaluation as the supplementary means on this issue. This paper designed a Hadoop platform for data collection and processing, and explored the social evaluation of innovative drugs based on big data analytics. Through the analysis of mined data and affective computing on online comments, a new Chinese drug extracted from marine organisms can be evaluated comprehensively by the proposed method. Furthermore, the potential utilization of fullerene materials may be considered for improving its curative effects. Research work of this paper provides a big data analytics method for social evaluation of innovative drugs as well as their promising improvements.

Key words

Big data analytics, social media, innovative drug, social evaluation, marine biology, fullerene materials

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Publication information

Volume 14, Issue 3 (September 2017)
Advances in Information Technology, Distributed and Model Driven Systems
Year of Publication: 2017
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Dai, G., Fu, X., Dai, W., Lu, S.: Social evaluation of innovative drugs: A method based on big data analytics. Computer Science and Information Systems, Vol. 14, No. 3, 805–821. (2017),