Abstract
Information sharing in the age of the Internet makes it impossible for the online public opinion to be neglected in the policy-making, analyzing and guiding the online public opinion reasonably and effectively have great significance to improving government administrative ability. “Delayed retirement age” has always been one of the hot topics in the public. Therefore, this article uses python to obtain Weibo texts, combines with the Baidu index to select the hot topics related to “delayed retirement age”, identifies three hot topics: “pension increase”, “pension insurance reform” and “ageing population”. Based on Latent Dirichlet Allocation, this article segments the Internet public opinion and selects relevant keywords under each hot topic, using text tendency analysis to analyze the public opinion from January to May in 2020. The empirical analysis of the online public opinion on the topic of “delayed retirement age” shows that the overall public opinion tendency from January to May is pessimistic. This article explains this result and gives corresponding suggestions.
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