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ZTE Communications ›› 2019, Vol. 17 ›› Issue (3): 2-8.doi: 10.12142/ZTECOM.201903002

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  • 收稿日期:2019-05-09 出版日期:2019-09-29 发布日期:2019-12-06

A Lightweight Sentiment Analysis Method

YU Qingshuang1, ZHOU Jie2, GONG Wenjuan1   

  1. 1.China University of Petroleum (East China), Qingdao, Shandong 266000, China
    2.Operation Coordination Department of Tianjin Branch of CNOOC (China) Co., Ltd., Tianjin 300000, China
  • Received:2019-05-09 Online:2019-09-29 Published:2019-12-06
  • About author:YU Qingshuang (yqs_18106301006@163.com) received the B.E. degree in Software Engineering from Qufu Normal University, China in 2019. He is currently pursuing a master’s degree in computer science at China University of Petroleum (East China). His research interests include data mining and deep learning. He once participated in the National College Student Innovation Competition and won the second prize.|ZHOU Jie is currently working at the Tianjin branch of China National Offshore Oil (China) Co., Ltd. (CNOOC). After graduating in 2006, he joined the offshore oil industry and worked in China Petroleum Environmental Protection Services (Tianjin) Co., Ltd. and CNOOC Tianjin Branch. His main research interests include understanding and resolving the contradiction between the sensitive areas of the three provinces and one city, the environmental protection zone, the main functional zoning of the ocean, and the offshore oil and gas exploration and development.|GONG Wenjuan received the B.E. degree in software engineering from Shandong University, China in 2004, the M.S. degree in computer graphics from Shandong University, China in 2007, and the M.S. and Ph.D. degrees in information technology from Autonomous University of Barcelona, Spain in 2013. From 2013 to 2014, she was a postdoctoral researcher with the Oxford Brooks University, UK. She is currently with China University of Petroleum (East China). Her research interests include computer vision, audio processing, machine learning, and quantum machine learning. She has published 14 SCI-indexed papers.


The emergence of big data leads to an increasing demand for data processing methods. As the most influential media for Chinese domestic movie ratings, Douban contains a huge amount of data and one can understand users’ perspectives towards these movies by analyzing these data. In this article, we study movie’s critics from the Douban website, perform sentiment analysis on the data obtained by crawling, and visualize the results with a word cloud. We propose a lightweight sentiment analysis method which is free from heavy training and visualize the results in a more conceivable way.

Key words: web crawler, microblog, text sentiment analysis, word cloud