采用超图的微博群落感知方法

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采用超图的微博群落感知方法

更新时间：2025-07-09

- 采用超图的微博群落感知方法
- Issue 11, Pages: 120-126(2012)
- 作者机构：
  
  北京大学软件与微电子学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP311.13;TP393.092
- Online First：10 November 2012，
  
  Published：2012
- 稿件说明：
移动端阅览
[J]. 2012, (11): 120-126.
DOI：

[J]. 2012, (11): 120-126. DOI：

摘要

针对微博群落的识别与形成演化机理的获取问题

提出一种基于超图的微博群落感知方法.归纳微博用户的交互关系

提出以用户为节点、交互关系为边的微博用户交互关系超图模型;分析微博用户交互环境的情境特征

通过FP-TREE方法挖掘用户交互与情境特征的关联规则;根据关联规则对超图模型进行划分

得到具有相同情境的微博群落.以新浪微博为例进行了模拟验证

结果表明该方法能够感知导致微博群落形成的情境特征

且较传统数据挖掘方法能够更加准确地识别微博群落.

Abstract

A method of micro-blog community awareness based on hypergraph is proposed to identify micro-blog community and explore its evolution mechanism. A hypergraph based relational model of micro-blog users is established by summarizing interactions among micro-blog users. Users are vertices

and interactions are edges in the hypergraph. Association rules among micro-blog interactions and context are mined using FP-TREE method by analyzing user profile and micro-blog message. Then

hypergraph is divided into communities with same context characters based on the association rules. A simulation test based on Sina micro-blog is performed to validate the effectiveness of the proposed method. The result shows that the method can be aware of the context of micro-blog community

and is more accurate than traditional data mining method in identifying the micro-blog communities.

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