"基于Python的B站用户行为分析系统——大数据分析与数据可视化"

基于Python的B站用户行为分析系统是通过利用Python技术开发的一款系统，用于对B站的用户行为数据进行分析和可视化。随着互联网技术的不断发展，网络用户数量迅速增加，网络数据也呈现爆发式增长。这些网络数据对于互联网企业来说具有巨大的商业价值，通过对数据的分析可以更好地了解用户需求，并基于用户需求制定经营策略，实现精准定位和价值创造。 本系统以B站作为数据源，通过大数据分析对B站中的UP主账号进行数据可视化。在数据可视化中，系统可以分析UP主最喜欢发布的视频类型、视频标签，以及UP主的粉丝数、获赞数等，通过柱状图等图形模式展示分析结果。此外，系统还可以对用户观看视频的内容进行分析，包括喜欢互动、喜欢分享以及一键三联等视频类型。通过这些分析，系统可以将粉丝榜、播放榜等进行均量和总量的图形展示，为企业提供数据支持，并为UP主和用户的观影行为提供有效的数据分析参考。 关键词：大数据、数据分析、B站、视频类型分析 Abstract: In recent years, with the continuous development of Internet technology, the number of Internet users has grown rapidly, and the amount of network data has also increased exponentially. These network data can provide high commercial value for Internet companies. By analyzing the data, Internet companies can better understand user needs and make business policy decisions based on these needs, achieving value creation services for the entire enterprise through precise positioning. This paper presents a system for analyzing and visualizing user behaviors on Bilibili (B站) using Python technology. The system is designed to analyze and visualize user behavior data from Bilibili. With the help of big data analytics, the system provides visualizations of Bilibili's UP main accounts' favorite video types, video tags, as well as the number of fans and likes. Various chart types, such as bar charts, are employed to present the analysis results. Additionally, the system also analyzes user preferences for video content, such as interactive videos, shared videos, and "one click for three" videos. By conducting such analyses, the system can present graphs of the average and total numbers of fans and views, providing data support for enterprises and effective data analysis references for UP main accounts and users. Keywords: big data, data analysis, Bilibili, video type analysis