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随着互联网快速发展，其应用和服务广泛渗透人民生活，网络社交平台作为人们发布观点的主要渠道，容易形成舆情对网络环境产生一定的影响。新冠肺炎疫情给全球经济带来了巨大的冲击，经济和社会发展受到影响。随着疫情得到遏制，国家重心重新回到经济和社会发展上，地摊经济重新被提起，不仅可以丰富人们的业余生活，也可以创造更多的就业岗位，促进经济发展。人们对地摊经济的讨论越来越多，“地摊经济”逐渐成为社会热点话题。而当前对于地摊经济的研究大多集中在地摊经济城市管理及发展现状等方面，本文从网络社交平台网民相关话题下发布内容及评论文本数据入手，了解民众对于地摊经济的看法，从网络舆情治理的角度，丰富地摊经济领域的研究内容。

本文在后疫情时代疫情防控常态化的背景下，以新浪微博网民发布相关内容数据为基础，对热点话题“地摊经济”进行研究。通过机器学习的方法了解社会公众对地摊经济的态度及关注点，协助政府及有关部门对相关政策做出调整，并积极引导网络舆情发展，同时也帮助人们了解话题发展趋势，引发正面的思考并做出正确的判断。主要采用了Python网络爬虫的方式，获取新浪微博社交平台2020年5月21日至2020年7月22日这一时间段内，关键词为“地摊经济”的发布内容数据及相关子话题下意见领袖微博的网民评论内容数据，对其文本内容进行自定义词典、去停用词及中文分词等数据预处理工作。在地摊经济话题实证分析中，根据网络舆情生命周期理论将热点话题舆情演变分为四个时期分别为酝酿期、爆发期、波动期和衰退期，分别对每个时期内主题及情感倾向进行分析，并提取子话题内意见领袖下微博评论文本数据进行词频及情感分析。研究发现，社会热点话题发展规律符合网络舆情生命周期理论，讨论内容呈现多话题联动规律，由主话题衍生出来的各个子话题之间存在一定的关联性，子话题情感及主题也会影响主话题的情感倾向及主题内容。网民情感得分从波动起伏较大到趋于平稳中受到意见领袖微博内容的影响，一定程度上影响了主题及情感得分走向。在社会热点话题的传播过程中，政府官方媒体等意见领袖的微博内容起重要作用，为各级政府合理引导网络舆情提供了参考和理论依据。

With the rapid development of the Internet, its applications and services have widely penetrated people's lives. As the main channel for people to publish their opinions, online social platforms are easy to form public opinions and have a certain impact on the network environment. The new crown pneumonia epidemic has brought a huge impact on the global economy, and economic and social development has been affected. With the containment of the epidemic, the country's focus has returned to economic and social development, and the street stall economy has been brought up again, which can not only enrich people's spare time, but also create more jobs and promote economic development. There are more and more discussions about the street stall economy, and the "street stall economy" has gradually become a hot topic in society. However, most of the current research on the street stall economy focuses on the urban management and development status of the street stall economy. This article starts with the content and comment text data published under the relevant topics of netizens on the online social platform, to understand the public's views on the street stall economy, from the Internet public opinion governance. From the perspective, enrich the research content in the field of stall economy.

In the context of the normalization of epidemic prevention and control in the post-epidemic era, this article is based on the relevant content data released by Sina Weibo, and conducts research on the hot topic "market stall economy". In order to understand the public's attitude towards the stall economy, help the government and relevant departments make adjustments to relevant policies in line with public opinion and actively guide the development of online public opinion, and also help people understand topic development trends and make correct judgments. The python web crawler is mainly used to obtain the published content data of the Sina Weibo social platform during the period from May 21, 2020 to July 22, 2020, with the keyword "Street Stall Economy" and related subtopics. Netizen comment data of opinion leaders' Weibo content, and data preprocessing such as custom dictionary, removal of stop words and Chinese word segmentation for text data.

In the empirical analysis of the topic of stall economy, according to the life cycle theory of Internet public opinion, the evolution of public opinion on hot topics is divided into four periods, namely the incubation period, the outbreak period, the volatility period and the recession period. The themes and sentiment tendencies in each period are analyzed separately. , And extract the text data of Weibo comments from opinion leaders in the subtopics for word frequency and sentiment analysis. Research has found that the development law of social hot topics conforms to the online public opinion life cycle theory. The discussion content presents the law of multi-topic linkage. There is a certain correlation between the various subtopics derived from the main topic. The emotions and themes of the subtopics will also affect the main topic. Emotional orientation and subject content. The sentiment score of netizens fluctuates from large fluctuations to stable, and is affected by the content of opinion leaders' microblogs, which affects the theme and the trend of sentiment scores to a certain extent. In the process of disseminating social hot topics, the microblog content of government official media and other opinion leaders plays an important role, providing a reference and theoretical basis for governments at all levels to rationally guide online public opinion.