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By analyzing microblog texts, a visual early warning research of college net loans is conducted in this paper to effectively reduce the negative impact of illegal Internet loans (abbreviated as "net loans") on college students' lives. Two calculation models are proposed in our research: One is the Identification Model of Risk Degree (IMRD) based on the security level of microblog texts about net loans. The other is the Calculation Model of Relationship Closeness (CMRC) based on three dimensions: user's relevant relationship, interaction strength, and interest similarity. IMRD is used to identify the risk of microblog net loan texts, and determine whether to early warn or not. CMRC is utilized to acquire a net loan communication map by describing the closeness level between net loan microblog publishers and their followers, and analyzing the possibility of retweeting. A visual monitoring and early warning platform is constructed based on these two models. With this platform, further spread of net loan information can be prevented by analyzing the graph and cutting off key nodes in time. The early warning mechanism of this research can effectively alleviate the negative influence of illegal net loans.

Price decision is studied in a risk-averse retailer-dominated dual-channel supply chain, which consisting of one manufacturers and one retailer with both off-line and on-line channels. Firstly, two mean-variance models in centralized and decentralized supply chain are established. Secondly, the optimal solutions under the two decision modes are compared and analyzed. The results shows that the price of dual-channel of retailer decreased with the increase of retailers’ risk- aversion coefficient and the standard deviation of the fluctuation of market demand, while the wholesale price changes is on the contrary; in addition, when the market demand is greater than a certain value, the prices of dual channel are correspondingly higher in decentralized supply chain than in centralized supply chain, and vice versa. In addition, when the retailer’s risk aversion is in a certain interval, the expected utility of the whole supply chain is greater in centralized supply chain than in decentralized decision, and vice versa. Finally, a numerical example is given to verify the above conclusions.