APP信息传播溯源技术的应用与实验分析

Application and Experimental Analysis of APP Information Dissemination Traceability Technology

对新闻APP进行溯源分析,挖掘高影响力用户,一方面可以提高热门新闻的传播面和影响力,另一方面也有助于监管部门明确舆论监管的重点对象。在新媒体监管日益严格的背景下,开展新闻APP信息传播溯源技术研究具有重要的现实意义。本文首先从通信流量捕获、数据采集分析、用户影响力计算等方面,介绍了新闻APP溯源分析系统的结构组成和基本功能,随后设计了数据采集实验和用户影响力评估实验。实验结果表明,本文所选3款主流新闻APP的数据爬全率均达到了90%以上,爬全率较为理想。基于NAUR算法的用户影响力排名质量要高于传统的PageRank等算法,在信息传播溯源方面表现更加优异。

The traceability analysis of news APP and the mining of high-influence users can improve the dissemination and influence of popular news on the one hand,and help the regulatory authorities to clarify the key objects of public opinion supervision on the other hand.Under the background of increasingly strict supervision of new media,it is of great practical significance to carry out research on the traceability technology of news APP information dissemination.This paper firstly introduces the structure,composition and basic functions of the news APP traceability analysis system from the aspects of communication traffic capture,data collection and analysis,and user influence calculation,and then designs data collection experiments and user influence evaluation experiments.The experimental results show that the data crawl rate of the three mainstream news apps selected in this paper has reached more than 90%,and the crawl rate is ideal.The quality of user influence ranking based on the NAUR algorithm is higher than that of traditional PageRank and other algorithms,and it performs better in information dissemination and traceability.