PageRank-based social contact big data information maximizing method

A big data and social network technology, applied in data processing applications, instruments, calculations, etc., can solve problems such as impact

Inactive Publication Date: 2017-09-01
SOUTH CHINA UNIV OF TECH
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

The current research on social network information maximization and related influence propagation models are based on friendl...

Method used

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  • PageRank-based social contact big data information maximizing method

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Embodiment

[0025] figure 1 Described is a flowchart of the method. The data set in this embodiment is Epinions, a social network data set provided by SNAP (Stanford Network Analysis Platform) with both friendly and hostile relationships.

[0026] Extract friendly and hostile relationships in social big data: In general, the check-in data of users in the data set is given in text and has some information that we don't need. Firstly, preprocessing is carried out, according to the information of the given social network data set, the adjacency relationship between all users is processed, and the adjacency matrix of the entire data set is obtained, where 1 represents the friendly relationship between two people, and -1 represents The hostile relationship between the two, 0 means there is no connection between the two. Then extract the adjacency matrix represented by friendly relationship and hostile relationship represented by 1 and -1 respectively, in which -1 in the hostile adjacency mat...

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Abstract

The invention discloses a PageRank-based social contact big data information maximizing method. According to the method, friendly relations and hostile relations in social contact big data are extracted; a PageRank algorithm is applied to a friendly relation adjacency matrix and a hostile relation adjacency matrix separately; and seed nodes are selected. The method is aimed at a social network with friendly relations and hostile relations; the influence of the hostile relations on information dissemination is considered; and the PageRank algorithm is adopted to calculate the difference of the PR value of the friendly relations and the PR value of the hostile relations, so that the influence of a user can be measured, and the effective seed node set is selected, and therefore, information can be spread in a maximized manner through the friendly relations and hostile relations in the online social network.

Description

technical field [0001] The invention relates to an information maximization technology, in particular to a method for maximizing information in a social network with both friendly and hostile relationships. Background technique [0002] With the development of the Internet and the popularization of mobile terminals, online social networks have gained rapid development and attention. The research on social network information maximization has very practical and practical significance. Using the friendly relationship and characteristics in social big data to carry out word-of-mouth marketing and "viral transmission" has become more and more the focus of research. It is used in marketing, advertising, etc. has very important applications. The existing social network information maximization technology mainly considers the friendly relationship in the social network, but does not consider the hostile relationship in the social network, such as the hostile relationship in the Ep...

Claims

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Application Information

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IPC IPC(8): G06Q50/00
CPCG06Q50/01
Inventor 何克晶陈书波
Owner SOUTH CHINA UNIV OF TECH
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