Research On The Online Advertising Decision Making Method About Associate With Users’ Influence Attributes

How to make use of social networking platforms to make online advertising for enterprises with the help of influential users and to maximize advertising performance is a hot issue in social marketing decision-making research. Since network users differ in background of knowledge, domain authority, social relations, the resources and capabilities of the network social relationship that users acquire are also different. Such differences are reflected in the varied scope and effect of each user’s network influence. Different individuals beget different network influences, and such differences are the result of a multitude of personal and social factors of the network users. Differences in user’s influence leads to differences in advertising performance that such user produce. Therefore, enterprises select target users from a great variety of influential ones to match expected advertising objectives, the adaptation association between the network influence attributes and advertising performance objectives must be considered, it is a multi-attribution decision-making optimization problem.From the perspective of social capital theory, this paper study users’ network influences and growth process in social capital resources. Find the association between user’s influence attributes which includes users’domain authorities, text qualities and interaction relationships and the advertising performance objectives in social network. To match the influential users to the appropriate online advertising objectives, the joint probability method and information distance transfer algorithm are used to calculate the "influential users-advertising performance objectives" association matrix and construct the multiple attribute decision-making model. It can obtain the association degrees between users’ influence and the advertising performance objectives, and can screen the target users. This paper will construct a set of methods of multiple attribute decision-making an its optimization for enterprises select seed users to make online advertising. This study is a new breakthrough in Internet marketing research field and of great significance in both theory and practice because it can enrich e-marketing theories, help enterprises make online advertisements with marketing decision supports, and get high-efficiency and high-benefit for companies.