Published online by Cambridge University Press: 10 September 2019
Applying a novel approach based on online query volume data, this study provides the first large-scale portrait of revolutionary nostalgia among the Chinese, undertaking an empirical analysis of how the aggregate level of nostalgia is shaped. For each Chinese province, we use the normalized frequency of searches for red songs on Baidu, the most widely used online search engine in China, to quantify the local level of nostalgia. We find that the evolving trends of nostalgia among the provinces are similar but stratified. The results from the dynamic panel data analysis using the Generalized Method of Moments indicate that revolutionary nostalgia is significantly affected by a set of socio-economic determinants, including GDP per capita, income inequality, social development, legal development and the degree of globalization.
基于网络在线搜索形成的海量数据,本研究绘制了第一幅当代中国人革命怀旧情绪的大幅肖像,并对各省怀旧情绪的形成机制进行了实证分析。对每一个省份,我们使用网民在中国国内最广泛使用的在线搜索引擎——百度上搜索红色歌曲的标准化频次来测量当地的革命怀旧水平。我们发现,各省之间怀旧情绪的演变趋势相似但也有分化。基于广义矩估计的动态面板数据分析的结果表明,革命怀旧情绪受到一系列社会经济因素的显著影响,包括省级层次的人均 GDP 、收入不平等、社会发展、法制发展以及全球化发展水平。