Title: Statistical analysis for user group of opposing traditional Chinese medicine in Weibo

Authors: Li Hao; Zhang Bingzhu; An Xuzhao; Ma Xingguang; Shen Junhui

Addresses: College of Management, Beijing University of Chinese Medicine, Beijing 100029, China ' College of Management, Beijing University of Chinese Medicine, Beijing 100029, China ' College of Management, Beijing University of Chinese Medicine, Beijing 100029, China ' College of Management, Beijing University of Chinese Medicine, Beijing 100029, China ' College of Management, Beijing University of Chinese Medicine, Beijing 100029, China

Abstract: With Western culture and science being widely accepted in China, Traditional Chinese Medicine (TCM) becomes a controversy. Therefore, it is very important to study the public's views on Traditional Chinese Medicine. The rapid development of online social networks, such as Sina Weibo, can quickly and easily provide a sample for emotional analysis. In this research, firstly, Sina Weibo's users of Traditional Chinese Medicine were collected, and their blogs were obtained. The blogs were automatically marked as supporting Traditional Chinese Medicine or opposing Traditional Chinese Medicine based on user tags. Then, blogs about Traditional Chinese Medicine were selected by using the Chinese word segmentation tool and Traditional Chinese Medicine dictionary. Finally, the Chinese word segmentation tool was used to count the words and find highest frequency of words in the blogs of opposing Traditional Chinese Medicine to explore hot topics and propose corresponding suggestions for the development of Traditional Chinese Medicine.

Keywords: emotional analysis; Chinese word segmentation tool; Traditional Chinese Medicine; Weibo; user tag; hot topics.

DOI: 10.1504/IJCAT.2020.111090

International Journal of Computer Applications in Technology, 2020 Vol.64 No.1, pp.108 - 113

Received: 29 Dec 2019
Accepted: 25 May 2020

Published online: 21 Oct 2020 *

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