基于文本挖掘的公共事件分析(2012-2014) ——类别、涉事者、地理分布及演化

张伦 钟智锦 毛湛文

国际新闻界 ›› 2014, Vol. 36 ›› Issue (11) : 34-50.

国际新闻界 ›› 2014, Vol. 36 ›› Issue (11) : 34-50.
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基于文本挖掘的公共事件分析(2012-2014) ——类别、涉事者、地理分布及演化

  • 张伦,中国科学院大学新闻传播学系讲师。电邮:zhanglun@ucas.ac.cn
    钟智锦,中山大学传播与设计学院副教授。电邮:zhongzhijin@hotmail.com
    毛湛文,中国人民大学新闻学院博士研究生。电邮:apple-42@163.com
    本文得到国家社会科学基金青年项目“社会化媒体中公共事件话语框架及其演化机制研究”(项目编号:14CXW015)的支持。
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What, Who, Where, and How: Text Mining of Public Events in China (2012-2014)

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摘要

本研究以2012-2014年间我国3359个公共事件为对象,利用描述统计、文本挖掘方法以及空间地理可视化呈现等方法,定量地描述公共事件的基本特征。研究发现,公共事件参与者身份、事件类型以及事件发生的空间地理特征皆呈现出不平等分布趋势。具体而言,涉事群体/个体身份多集中于政府部门、官员和公检法机关;事件类型中“制度危机与社会公平类”问题占有压倒性优势;从地理分布来看,公共事件多发生于经济较发达地区;从事件演化模式来看,不同类别的事件呈现出竞争关系,即大部分事件发生频度呈负相关关系。

Abstract

This study describes the dynamic pattern and the features (i.e., what, who, and where) of public events happened in China during the last two years. The data were extracted from two independent databases of Chinese public event. By analyzing the 3,359 cases using descriptive statistics and text mining techniques, this study found that the event type, the identity of involved social groups/individuals, and the geographical location of public events are severely unequally distributed. In specific, the event type that most frequently happened is the events regarding “institutionalization crisis and social equality”; the location where public events often occurred concentrate on developed regions, such as the Southeast Coast; and the identities of deeply involved social groups/individuals include government departments and officers, public security organs, procuratorial organs, people's courts, and ordinary people. In addition, it is found that the frequency of different types of public events competed with each other during the past two years as evidenced by the negative correlation coefficients of event frequency across event types.

关键词

公共事件 / 文本挖掘 / 演化模式

Key words

public events / text mining / dynamic pattern

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导出引用
张伦 钟智锦 毛湛文. 基于文本挖掘的公共事件分析(2012-2014) ——类别、涉事者、地理分布及演化[J]. 国际新闻界. 2014, 36(11): 34-50
ZHANG Lun ZHONG Zhijin MAO Zhanwen. What, Who, Where, and How: Text Mining of Public Events in China (2012-2014)[J]. Chinese Journal of Journalism & Communication. 2014, 36(11): 34-50

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