Research And Implementation Of Social Media Marketing System Based On User Influence

With the development of the Internet,social media has become the main channel for people to obtain information,and the internet word-of-mouth has become an important reference for consumers to purchase products and services.Therefore,more and more companies choose to conduct word-of-mouth marketing on social media.However,the process of information dissemination in social media is very complicated.How to put the marketing information to get the best publicity effect is the key issue of social media brand marketing.This article conducts research on this and implements a social media marketing system based on user influence.The main research contents are as follows:(1)We propose a theme-based user influence analysis algorithm.The algorithm uses the similarity of subject interests between individuals to determine the willingness of individuals to forward information,and can calculate the influence and relative ranking of individuals.In addition,the individual's willingness to forward can provide support for building an information dissemination model.(2)Considering the issue of maximizing influence in a competitive scenario,we construct a competitive propagation model.We have designed a competitive influence maximization algorithm,which selects the node set as the target of marketing information.Compared with traditional algorithms,this algorithm solves faster.This can avoid waiting too long in practical applications(3)We design and implement a social media marketing system.This system can collect social information to provide data support for user influence analysis algorithms,and can automatically release information delivery tasks,including operations such as posting,reposting,commenting,and liking.In order to improve the ability to release information and ensure the effectiveness of marketing promotion,the system provides tasks management,account management,account cultivation and other functions.Finally,we tested the functionality of the system in a real social network.Experimental results show that the system can improve the efficiency of sending marketing information and improve the effectiveness of social media marketing.This system has important application value.