This study is to help We-Media to improve the users' attention by using Big Data technology. A new TAM model is optimzed based on the TAM model proposed by Shein Bowman and Chirs Willis. The model can better obtain the users' data and optimize We-Media to attract more attention. The paper took Guangdong University of Foreign Studies as an example and carried out experiments. We applied MapReduce and Hadhoop to process the Big Data, such as the users' interests, hobbies and browse habits of We-Media users with SPSS. The above processes are completed by using literature research, empirical research, quantitative analysis and qualitative analysis. The experiment result can help We-Media to improve its content. We-Media can optimize the released content according to the users' Big Data, so as to obtain the users' higher attention, assist people to recognize things positively and promote the direction of We-Media.