Method for automatically screening influential users on social media networks

A social media and automatic screening technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as influence modeling that does not consider subject sensitivity

Active Publication Date: 2013-04-03
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Claims
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Problems solved by technology

On the other hand, the traditional method is to model the general influe

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  • Method for automatically screening influential users on social media networks
  • Method for automatically screening influential users on social media networks
  • Method for automatically screening influential users on social media networks

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[0075] In order to evaluate the present invention, an embodiment of the present invention is based on the API interface of Flickr, an interest-based social media photo sharing website, and 2,314 users, and a total of 556,942 pictures were captured. Figure 6a Representative users who are influential in four topics screened by the method of the present invention are shown. Each topic is learned with a hypergraph regularized topic probability model, represented by the most prominent word, the more relevant and important the word, the larger its font. From Figure 6a It can be seen that the four themes are respectively related to flowers, girls, cities, and beach scenes. Under each topic, the user with the highest influence score and his picture with the highest influence score under the topic are listed. It can be seen from the figure that the topic vocabulary is related to the picture. Figure 6b Representative pictures of influence in four subjects screened by the method of ...

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Abstract

The invention provides a method for automatically screening influential users on social media networks. The method comprises the following steps of: modeling for users, interested objects and interaction relationship between the users and the interested objects by a hypergraph model; automatically learning to obtain a connotative interest topic by using a regularization topic probability model of hypergraph restraints and taking the similarity relationship between the content information and the content information of the interested objects as restraints; and performing topic influence sorting on each user and interest object, propagating topic influence by using a similarity propagation model, the users and the interest objects on the hypergraph and the hyperedge between the users and the interest objects until to reaching a steady state, and then sorting to obtain the influential users under specific topics. By the method, the distribution of the user influence in the social media network can be truly and accurately reflected.

Description

technical field [0001] The invention belongs to the technical field of digital information processing, and in particular relates to a social media network data screening technology, in particular to a screening method for theme-sensitive and influential users based on multimedia content and link analysis. Background technique [0002] The advent and prosperity of social media networks has changed the way people obtain and consume information. Various social media networks provide a platform for people to easily create and share interesting content. For example, Sina and Tencent Weibo share text messages, twitter text messages, and Flickr picture sharing, etc. However, an obvious problem is that while people obtain information conveniently, they also face the problem of information overload. When people obtain information, they tend to obtain the content they are interested in and use influential users as information sources. Screening out influential users or objects of i...

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Application Information

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IPC IPC(8): G06F17/30
Inventor 徐常胜桑基韬方全
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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