The Reae Arch And Implementation Of Information Propagation And Tracebility Technology Of News Applications

News apps enable people to obtain news information anytime and anywhere,greatly enriching people's access to information,and has received more and more attention in recent years.However,the news app spreads a large amount of news in a timely manner,and it also promotes the dissemination of various information that has not been reviewed in time.Traceability analysis of information dissemination helps to cut off the transmission of bad information in a timely manner and provides effective support for maintaining the sustainable and healthy development of the mobile Internet ecosystem.This paper studies the method of news tracing analysis of mobile news apps.By constructing heterogeneous social network and improving PageRank algorithm,we can get the nodes with high influence in the process of information dissemination and public opinion formation,and timely control the specific information dissemination in news apps.The main work of this paper is as follows:(1)Research on news apps data capture method based on reverse analysis of communication protocol.Since the communication protocols between the mobile news apps and the server-side are not disclosed,and the communication protocol packets have some encryption parameters,the traditional data-oriented method for the Web pages cannot be directly applied to the news apps.In order to solve this problem,this paper proposes a method based on conmmunication protocol reverse analysis.Firstly,the key function is located by static analysis,then the encryption method of the parameters in the key function is determined through dynamic debugging.After obtaining the key parameters,the client and the server are simulated to communicate and the data are captured.(2)Study the heterogeneous network construction method including user and news nodes.In the construction of the social network part,the existing methods usually consist of the user as the only type of node to form a social network,and then analyse the network based on the network topology,but the actual information dissemination involves more than one type of subject,the information contained in a homogeneous network is not comprehensive enough to cause information loss.Based on this situation,this paper constructs a heterogeneous network composed of user nodes and news nodes.The heterogeneous network contains more comprehensive structural information and rich semantic information,which can make the analysis results more comprehensive and accurate.(3)Study the user influence evaluation method based on NAUR algorithm.In the process of calculating the influence of nodes,this paper combines the characteristics of network topology and user behavior for common analysis.Most of the user's interaction behavior occurs in the period of short interval of events,which satisfies the power law distribution.For this reason,this paper uses exponentially truncated power law function to fit the law between user interaction behavior and time interval,and proposes NAUR algorithm to calculate the influence of the user nodes by combining the above rule with the PageRank algorithm based on the idea of random walk.(4)Development of information dissemination source system for news apps.When given specific topics or message data,the system developed in this paper can trace the key nodes in the topic propagation process based on data acquisition,heterogeneous network construction and user impact assessment,and then we can build a critical path for message dissemination and achieve traceability.The experimental results show that the proposed method has high efficiency and accuracy.