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The mathematical models are built to predict the growth trend of public accounts corresponding to different fields, and to evaluate whether Web-Chat operate their platforms effectively. Four domains of public account information are chose which are representative in public web-chat accounts, these areas are education, government, media and network. Secondly, the number information of those fields are used and handled them. Finally, based on the dispersed gray model as the foundation, that is DGM (2,1). What’s more, error rationality C is calculated, that are 0.43, 0.42, 0.53, 0.61 and the error probability P are 0.89, 0.86, 0.75, 0.88 respectively in four different fields. We found that the model DGM(2,1) is better than GM(1,1) in forecasting rising trend of Web-Chat in different fields. In order to evaluate whether Web-Chat users operate their platforms effectively, the model is set up which combines the structure equation with comprehensive evaluation method to solve the problem. To test the model, five different fields are pick up, namely, government, education, media, website and celebrity. The result of the model shows that users in the fields of education and celebrity run their public web-chat accounts exceedingly effectively and the public accounts don’t work well in other three fields. Introduction Web-chat is a mobile text and voice message communication service developed by Tencent in China, first released in January 2011. Up to August 2014, there have been 438 million active domestic users and 70 million foreign loggers. It is worth noting that the users of public web-chat account allowed to send one message to common people everyday, but only a very few public accounts use the only chance to sent their group messages to common people. the majority of users of public account would send valuable news which they think worthy of attention and interesting messages which they think that audience may be interested in ,based on their own topics and target content. It is important for the companies to analyze whether they operate their platforms effectively and whether they would have made better use of the public platforms since there are numerous public accounts in various fields. In this paper we have researched to build mathematical models to solve the following tasks: (1) Looking for references to analyze the fields of Web-chat public accounts and model to predict the growth trend of public accounts corresponding to different fields. (2) Setting up a model to analyze whether public accounts in different fields are effectively run and explain the advantages and disadvantages of model. The establishment and solution of model in task 1 In order to predict the growth trend of number of media, government, education, network public International Conference on Education, Sports, Arts and Management Engineering (ICESAME 2016) © 2016. The authors Published by Atlantis Press 1284 account registrations, we choose 8 consecutive months of public accounts in each field on 2015 September as the original sequence, and constructed the forecasting model DGM (2,1) [1]. 1. Each field of the original sequence ) 0 ( k X is as follows: Tab.1 The registered amount of media, government, education, network 2015.0 9.04 2015.0 9.05 2015.0 9.06 2015.0 9.07 2015.0 9.08 2015.0 9.09 2015.0 9.1

Research on Assessing Public Web-chat Accounts based on the Dispersed Gray Model and Comprehensive Evaluation Model