Topic influence individual digging method based on relational network

A relational network and relational technology, which is applied in the field of topic influence individual mining in Weibo, can solve the problems that it is difficult to describe the relative influence of users and ignore the link structure of multi-relationship networks.

Active Publication Date: 2013-06-26
NAT UNIV OF DEFENSE TECH
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AI Technical Summary

Problems solved by technology

[0006] In Reference 2 "[2] Pal A, Counts S. Identifying topical authorities in microblogs [C] / / Proc of the 4th ACM International Conference on Web Search and Data Mining. New York, NY: ACM, 2011:45-54" In order to identify the authoritative users of each topic in Twitter, Pal et al. considered multiple attributes of users in Twitter, but ignored the link structure of multi-relational networks, making it difficult to describe the relative influence of users in the entire network

Method used

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  • Topic influence individual digging method based on relational network
  • Topic influence individual digging method based on relational network
  • Topic influence individual digging method based on relational network

Examples

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Embodiment Construction

[0027] A preferred embodiment of the present invention will be described in detail below with reference to the accompanying drawings, taking a microblog application as an example.

[0028] In order to comprehensively measure the user's influence on a certain topic level, the present invention considers various network relationship types in microblogs. For example figure 1 As shown in (a), the influence of user B on user A is manifested in four relationship types: 1) user A uses similar "RTB" or "viaB" in his blog post, and reposts user B's blog post; 2) user A A used similar "B" in his blog post, and replied to user B's blog post; 3) User A copied user B's blog post without explicitly using reposting tags such as "RTB" or "viaB"; 4) User A reads User B's blog post. exist figure 1 (a) shows 4 different types of directed edges (A, B) between users A and B to represent the above four types of relationships respectively. figure 1 (b) shows another example multi-relational netw...

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Abstract

The invention discloses a method for determining whether passages issued by network users have copy relations or not. The method includes: acquiring time probability distribution obeyed by time intervals of two passages with clear forwarding relations; deducing time probability distribution obeyed by time intervals of two passages with copy relations according to the acquired time probability distribution; setting a range which needs to be satisfied by time intervals of the two passages with copy relations according to the deduced time probability distribution; for optional two passages whose time intervals are in the range, calculation the similarity of the two; and determining whether the two passages have copy relations according to the similarity.

Description

technical field [0001] The invention relates to the technical field of network data mining, and in particular to the mining technology of topic influence individuals in microblogs. Background technique [0002] Twitter-like microblogging services have recently developed rapidly as a new communication medium. According to statistics from the 29th China Internet Report: By the end of December 2011, the actual number of microblog users in my country reached 250 million, an increase of 296.0% over the end of the previous year. , the utilization rate of Internet users is 48.7%. Different from other Facebook-like social network services, the social network relationship of Weibo service is one-way, and users can follow them without other user permissions. For example, the social network in Twitter is formed by the relationship of following (following). People who a user follows are called friends of the user; people who follow a user are called followers of the user. ) will appear...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/08G06F17/30
Inventor 丁兆云贾焰杨树强周斌韩伟红李爱平韩毅李莎莎
Owner NAT UNIV OF DEFENSE TECH
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