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| Text Mining on the Government Work Reports of the State Council (1954-2017) and Social Transformation Research |
| Wei Wei, Guo Chonghui, Chen Jingfeng |
| Institute of Systems Engineering, Dalian University of Technology, Dalian 116024 |
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Abstract The government work report of the State Council is a comprehensive policy text. This paper uses text mining technology to carry out a comprehensive multi-granularity, multi-level quantitative analysis of the government work reports. This has immense practical significance for acquiring an understanding of the evolution of domain content and the laws of social transformation discovery to relevant personnel. Firstly, a series of text preprocessing is done by using the Chinese word segmentation tool combined with three kinds of dictionaries created by us: the domain dictionary, the stop word dictionary, and the thesaurus dictionary. Then, frequent words, hot words, and new words are redefined and three kinds of corresponding feature mining methods are proposed. A quantitative calculation method for social vitality is proposed based on these new words, and then clustering analysis is conducted for feature words represented by a time series with a popular clustering method. According to the document information of the government work reports, we divide the time period from 1954 to 2017 into different stages, using which we conduct the pattern discovery for feature words combined with the feature words clustering results. Finally, our findings show that the selected frequent words, hot words, and new words in the government work reports can indicate the common problems, the hot issues and its evolution pattern, and the changes in social activity over the years. From the term clustering results and the reasonable time stages of the whole period, we get nine specific patterns of feature words.
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Received: 27 July 2017
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