Social network rebating method based on electronic commerce

Abstract

The invention belongs to the field of Internet finance, and discloses a social network rebating method based on electronic commerce. The social network rebating method is used for improving the unreasonable rebating situation caused by a multi-level distribution mode adopted in an existing social shopping platform. The method comprises the following steps: firstly, determining a corresponding object as a node in a social network, forming connection between nodes according to an information chain in the social network, and forming a relationship network by the connection between the nodes. Thenodes have characteristic values; in the relationship network, an influence coefficient corresponding to the connection exists between two nodes which are connected; after any node reaches a specificbehavior, a corresponding weight is calculated according to the influence coefficient of a node connected with the node; and the rebating amount generated by the specific behavior is allocated to thecorresponding node according to the weight ratio, so relatively fair social rebating is realized.

Description

technical field [0001] The invention belongs to the technical field of Internet finance, and in particular relates to a rebate method for social network shopping. Background technique [0002] With the increasing social value of the Internet, the original e-commerce format of traditional e-commerce, which is centered on [goods] and built around the commodity supply chain, has begun to appear to be growing weaker. In order to adapt to the current social shopping environment, social e-commerce has gradually emerged. [0003] The so-called social e-commerce refers to the application of social elements such as attention, sharing, recommendation, and interaction to e-commerce formats through the social functions of social network platforms or e-commerce platforms. It is a new type of e-commerce based on social relationships. business form. Through social interaction, user sharing and fission communication, word-of-mouth effect is first formed, trust relationship is established,...

AI Technical Summary

Problems solved by technology

[0011] However, the current multi-level rebate method of social e-commerce shows that no matter whether there is a relationship between the consumption purchase behavior and the cross-level personnel, as long as the individual is at the upper level of the social network structure, it can be based on the level of the network where it is, as agreed in advance. The commission rebate coefficient can obtain the corresponding multi-level commission remuneration, and due to the large number of its lower levels, this leads to the individuals at the upper level can easily obtain a large number of multi-level rebates, thus making the lower-level groups direct shopping guide enthusiasm Gradually decline, and form a social branch of "pulling people's heads", and finally collapse completely due to the inability to form a sustainable social e-commerce network system, and even cause adverse social impact

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