Abstract:

This paper analyzes the network attention on Shanghai's red resources using 19,048 comments collected from the Weibo platform between 2011 and 2024. The study examines fine-grained semantic interaction topics and proposes a new semantic and emotional interaction analysis framework, combining keyword topic extraction and text sentiment analysis methods. It explores the temporal evolution characteristics, content topic distribution, and emotional expression of online comments on Shanghai's red resources from multiple dimensions. The findings reveal: ① The online attention on Shanghai's red resources exhibits a long-tail distribution, with a growing trend in the number of comments over the years, closely interacting with city events and festivals; ② The content of online comments covers a wide range of topics, with particular attention to transportation, travel, exhibition content, and carrier innovation, displaying multidimensional features; ③ Sentiment analysis shows that positive emotions dominate the online comments, especially when social activities and interactive elements are integrated into red tourism routes, enhancing visitors' multiple experiences and social identification with red resources. Through data-driven text mining, this paper aims to expand the research methods on red resources and enrich the study of Shanghai's urban culture.

Key words: red resources, Shanghai, Weibo data, network attention, fine-grained text mining

摘要：

本文利用微博平台上收集的2011—2024年间19 048条关于上海红色资源的评论数据，分析上海红色资源网络关注度，研究细粒度语义交互主题，提出一种新的语义与情感交互分析框架，结合关键词主题抽取和文本情感分析方法，从多个维度探讨上海红色资源的网络评论时序演变特征、内容话题分布及其情感表达。研究发现：①上海红色资源的网络关注度呈现长尾分布特性，评论数量年际变化呈增长趋势，并与城市节事活动密切互动；②网络评论内容涵盖广泛，尤其关注交通与出行、展陈内容与载体创新等方面，呈现多维度特征；③情感分析表明，正向情感在网络评论中占据主导地位，特别是在红色旅游路线中加入社会活动和互动环节，游客呈现多重体验以及对红色资源的社会认同感。文章借助微博数据进行文本挖掘，以期拓宽红色资源研究的方法，丰富上海城市文化的研究内容。

关键词: 红色资源, 上海, 微博数据, 网络关注度, 细粒度文本挖掘