基于Python的B站用户行为分析系统数据分析论文【20~40字】

随着互联网技术的不断发展，网络用户数量迅速增长，导致网络数据规模呈现爆炸式增长。这些海量网络数据蕴含着极高的商业价值，通过数据分析，互联网企业能更好地了解用户需求，制定经营策略，并实现精准定位以创造更大的价值。本文基于Python技术，设计了一款B站用户行为分析系统，以B站数据作为数据源，通过大数据分析对UP主账号进行数据可视化分析。通过系统开发，可以分析UP主最喜欢发布的视频类型、视频标签，以及粉丝数、获赞数等数据，并以柱状图等图形方式展示。同时，系统还对用户观看视频内容进行分析，包括互动、分享喜好，以及视频类型偏好。通过分析结果，将粉丝榜、播放榜等数据以图形展示形式呈现，为企业提供数据支持，为UP主和用户观影行为提供有效数据分析参考。关键词：大数据、数据分析、B站、视频类型分析。In recent years, with the continuous development of Internet technology, the number of Internet users has grown rapidly, and the volume of network data has multiplied. These network data can provide high commercial value for Internet enterprises. Through data analysis, Internet enterprises can better understand user needs, make operational decisions based on user needs, achieve value creation services for the entire enterprise through precise positioning. This article is based on Python technology to design a system data analysis system that uses B station data as the data source and uses big data analysis to visualize UP primary account data. In data visualization, through this system development, UP's favorite video types, video tag analysis and UP main fan number, like The number of likes and other analysis is presented in the form of bar charts and other graphical modes. In addition, this design also needs to analyze user viewing content, including video types that like interaction, sharing, and one-click three-link. Through this analysis, fan lists, play lists, etc. can be displayed in terms of average and total amount. At the same time, it provides data support for enterprises in need and effective data analysis references for corresponding UP owners and user viewing behaviors. Keywords: big data; data analysis; B station; video type analysis.