面向话题的微博网络测量研究

刘玮; 王丽宏; 李锐光

doi:10.3969/j.issn.1000-436x.2013.11.019

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面向话题的微博网络测量研究

学术通信

- 面向话题的微博网络测量研究
- Topic-oriented measurement of microblogging network
- 通信学报 2013年34卷第11期页码：171-178
- 作者机构：
  
  1. 中国科学院计算技术研究所，北京 100190
  2. 中国科学院大学，北京 100049
  3. 国家计算机网络应急技术处理协调中心，北京 100029
- 作者简介：
  
  [ "刘玮（1984-），女，湖北武汉人，中国科学院博士生，主要研究方向为Web数据挖掘、智能信息处理等。" ]
  [ "王丽宏（1967-），女，辽宁沈阳人，国家计算机网络应急技术处理协调中心副总工程师、研究员、博士生导师，主要研究方向为网络信息安全、智能信息处理等。" ]
  [ "李锐光（1979-），男，山西阳泉人，硕士，国家计算机网络应急技术处理协调中心工程师，主要研究方向为网络与信息安全。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61170230);国家科技支撑计划基金资助项目(2012BAH46B01)
- DOI：10.3969/j.issn.1000-436x.2013.11.019
  中图分类号： TP393.08
- 网络出版日期：2013-11，
  
  纸质出版日期：2013-11-25
- 稿件说明：
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刘玮, 王丽宏, 李锐光. 面向话题的微博网络测量研究[J]. 通信学报, 2013,34(11):171-178.

Wei LIU, Li-hong WANG, Rui-guang LI. Topic-oriented measurement of microblogging network[J]. Communication journal, 2013, 34(11): 171-178.
刘玮, 王丽宏, 李锐光. 面向话题的微博网络测量研究[J]. 通信学报, 2013,34(11):171-178. DOI： 10.3969/j.issn.1000-436x.2013.11.019.

Wei LIU, Li-hong WANG, Rui-guang LI. Topic-oriented measurement of microblogging network[J]. Communication journal, 2013, 34(11): 171-178. DOI： 10.3969/j.issn.1000-436x.2013.11.019.

摘要

针对话题生成网络的动态时序特性，设计定量计算方法，从微博内容、网络结构、用户行为角度开展面向话题的新浪微博网络测量研究，结果发现：少数微博被大量转发，转发次数与对应微博数呈现近似的幂率分布；话题热度呈现明显的突发性和变化趋势，局部波动率能够有效地在大量背景微博中发现突发话题；基于话题生成的转发网络的小世界特性并不明显，且密集的关注关系不一定引发频繁的转发行为；传播能力强的话题中含有较大比例的持续参与用户，用户行为的话题相关性能够有效检测潜在关键用户。测量结果有助于了解话题生成网络的内容传播特点、网络结构特性及用户行为模式，测量指标能够有效应用于微博话题影响力分析等相关研究。

Abstract

According to the dynamic and temporal characteristics of the topic-generated network

a method of quantitative calculation was designed

and then the topic-oriented research on the network measurement technology from many aspects such as the features of the content was conducted

as well as the network topology and the characteristics of the user behavior. The experiments on the SINA microblog showed four new results. The first is that only a small portion of tweets has been forwarded broadly and the number of retweets follows the power-law distribution. The second is that the tweets' number of one topic is episodic and changing frequently

and the burst topic can be detected by the local volatility feature found in the massive background microblog data. The third is that the small-world feature in the topic-generated retweeting network is not obvious

and the dense relationship doesn't necessarily induce the frequent retweeting behavior. The fourth is that the topic which has been propagated broadly usually has a portion of the consistently participating users

and the correla-tion of the user behavior can be used to detect the potential and important users. The experimental results are helpful for un-derstanding the propagating mode

the structural chara and the pattern of the user behavior in a topic-generated net-work

and the indicators measured in the experiment can also be effectively applied in the future analyses.

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references

http://www.cnnic.cn/gywm/xwzx/rdxw/rdxx/201302/t20130222_38842,htm http://www.cnnic.cn/gywm/xwzx/rdxw/rdxx/201302/t20130222_38842,htm [EB/OL ] .

BAKSHY E , HOFMAN J M , MASON W A , et al . Everyone's an influencer: quantifying influence on twitter [A ] . Proceedings of the Fourth ACM International Conference on Web Search and Data Min-ing [C ] . 2011 . 65 - 74 .

KWAK H , LEE C , PARK H , et al . What is twitter,a social network or a news media [A ] . Proc of the 19th Int Conf on World Wide Web [C ] . New York , 2010 . 591 - 600 .

CHEW C , EYSENBACH G . Pandemics in the age of twitter: content analysis of tweets during the 2009 H1N1 outbreak [J ] . PLoS One , 2010 , 5 ( 11 ): 1 - 13 .

REN Z , LIANG S , MEIJ E , et al . Personalized Time-Aware Tweets summarization [A ] . Proceedings of the 36th International ACM Sigir Conference on Research and Development in Information [C ] . 2013 .

PATIL A , LIU J , GAO J . Predicting group stability in online social networks [A ] . Proceedings of the 22nd International Conference on World Wide Web [C ] . 2013 . 1021 - 1030 .

GRABOWICZ P A , AIELLO L M , EGUÍLUZ V M , et al . Distin-guishing topical and social groups based on common ide ity and bond theory [A ] . Proceedings of the Sixth ACM International Conference on Web Search and Data mining [C ] . 2013 . 627 - 636 .

JAVA A , SONG X , FININ T , et al . Why we twitter: understanding microblogging usage and communities [A ] . Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and So-cial Network Analysis [C ] . 2007 . 56 - 65 .

樊鹏翼，王晖，姜志宏等 . 微博网络测量研究 [J ] ．计算机研究与发展 , 2012 , 49 ( 4 ): 691 - 699 .

FAN P Y , WANG H , JIANG Z H , et al . Measurement of microblog-ging network [J ] . Journal of Computer Research and Development , 2012 , 49 ( 4 ): 691 - 699 .

KEMPE D , KLEINBERG J , TARDOS E . Maximizing the spread of influence through a social network [A ] . KDD [C ] . New York, USA 2003 . 137 - 146 .

田家堂，王轶彤，冯小军 . 一种新型的社会网络影响最大化算法 [J ] ．计算机学报 , 2011 , 34 ( 10 ): 1956 - 1965 .

TIAN J T , WANG Y T , FENG X J . A new hybrid algorithm for influ-ence maximization in social networks [J ] . Chinese Journal of Comput-ers , 2011 , 34 ( 10 ): 1956 - 1965 .

HE X , SONG G , CHEN W , et al . Influence Blocking Maximization in Social Networks Under the Competitive Linear Threshold Model [R ] . Technical Report , 2012 .

陈浩，王轶彤 . 基于阈值的社交网络影响力最大化算法 [J ] ．计算机研究与发展 , 2012 , 49 ( 10 ): 2181 - 2188 .

CHEN H , WANG Y T . Threshold-based heuristic algorithm for influ-ence maximization [J ] . Journal of Computer Research and Develop-ment , 2012 , 49 ( 10 ): 2181 - 2188 .

BARBIERI N , BONCHI F , MANCO G . Topic-aware social influence propagation models [A ] . Data Mining (ICDM), 2012 IEEE 12th Inter-national Conference on [C ] . New York, USA 2012 . 81 - 90 .

http://www.keenage.com/html/c_index.html http://www.keenage.com/html/c_index.html [EB/OL ] .

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