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社会态度反映了民众对社会的判断和感受,是社会治理需要高度重视的内容。文章对传统社会调查方法的优劣进行了分析,进而指出基于互联网计算社会态度在理论和现实层面的可行性。本文介绍了中科院心理所课题组基于网络行为的社会态度计算模型,并应用该模型计算了广东省的社会态度,通过广东省各个城市的“地方经济满意度”这一社会态度指标与该区域的宏观经济指标的相关性进一步验证了模型的可解释性。同时介绍了美国宾夕法尼亚大学通过Twitter数据预测公民幸福感并绘制美国的幸福感地图。利用预测模型的计算方法所采用数据真实客观,排除了社会赞许性等因素的影响,并极大地降低了成本,缩短了原有的调研周期,初步实现了社会态度的实时计算感知,对长期动态监控各项社会态度指标有极大的现实意义。希望能够与线下的社会调查法优势互补,共同为社会治理提供辅助决策。
Social attitudes reflect the people’s judgment and feelings about the society, which is the content that social governance needs to attach great importance to. The article analyzes the pros and cons of traditional social survey methods, and then points out the feasibility of calculating social attitudes based on the Internet at the theoretical and practical aspects. This article introduces the calculation model of social attitude based on Internet behavior of the Task Force of Chinese Academy of Social Sciences and calculates the social attitude of Guangdong Province through this model. By means of the social attitude index of “local economic satisfaction” in each city in Guangdong Province, The relevance of regional macroeconomic indicators further validates the model’s interpretability. At the same time introduced the United States University of Pennsylvania through Twitter data to predict the happiness of citizens and draw the United States happiness map. The data used in the calculation of the prediction model are objective and objective, excluding the influence of social approval and other factors, greatly reducing the cost and shortening the original research cycle, and initially realizing the real-time computing perception of social attitude. The long-term dynamic It is of great practical significance to monitor various social attitudes and indicators. Hope to be able to complement each other with the social survey law under the line, together to provide support for social governance decision-making.