收稿日期: 2016-11-01
修回日期: 2016-12-29
网络出版日期: 2017-01-20
基金资助
本文系国家社会科学基金重大项目“智慧城市应急决策情报体系建设研究”（项目编号：13&ZD173）和中央高校基本科研业务费项目“面向应急决策的专家发现与意见融合研究”（项目编号：CCNU16A05044）研究成果之一。
The Analysis of Niche Experts' “Stability-Change” Feature Under Different Semantic Environments: An Empirical Analysis Based on MetaFilter Dataset
Received date: 2016-11-01
Revised date: 2016-12-29
Online published: 2017-01-20
[目的/意义] 社交媒介不仅提供了用户间知识交流的平台，而且形成了知识复用的渠道。一部分社交网络用户在信息传播、知识共享等方面都能够对其他用户产生影响，称之为“小众专家”。对“小众专家”群体的研究对于社交网络中信息传播具有促进作用。[方法/过程] 以MetaFilter数据集为例，利用用户社交网络活动数据，生成用户关系网络，结合网络分析与时序分析筛选“小众专家”，分析“小众专家”群体在不同语义环境下的“稳定-迁移”特征，并提出评测指标，进行验证分析。[结果/结论] 结果显示：只有极少部分“小众专家”能够在多种语义环境下保持稳定性，而大部分“小众专家”只能在单一语义环境中保持稳定性。
李纲 , 张岩 , 叶光辉 . 不同语义环境下“小众专家”群体“稳定-变化”特征分析——基于MetaFilter的实证分析[J]. 图书情报工作, 2017 , 61(2) : 99 -106 . DOI: 10.13266/j.issn.0252-3116.2017.02.013
[Purpose/significance] Social media not only provides a platform for knowledge exchange for users, but also forms a channel for knowledge reuse. Some social network users can affect others in information communication and knowledge sharing. These users are called "niche experts". The study of "niche experts" helps to promote information dissemination. [Method/process] In this paper, the authors made use of user activity data from a popular community weblog named MetaFilter to construct social network. Then the authors got the niche experts by network analysis and time series analysis and analyzed the "stability-change" feature of niche experts under different semantic circumstances. The paper also introduced an index to measure this feature and it was proved to be correct. [Result/conclusion] The result of the study shows that only few niche experts can maintain stability under multiple semantic circumstances and the majority of niche experts can maintain stability only under single semantic circumstance.
[1] 孙茜.Web2.0的含义、特征与应用研究[J].现代情报,2006(2):69-70,74.
[2] 韩佳,肖如良,胡耀,等.在线社交网络中信息传播模式的特征分析[J].计算机应用,2013,33(1):105-107,111.
[3] MIKA P, ELFRING T, GROENEWEGEN P. Application of semantic technology for social network analysis in the sciences[J]. Scientometrics, 2006, 68(1):3-27.
[4] SLEEMAN J, FININ T. Computing FOFA co-reference relations with rules and machine learning[C]//Proceedings of the 3rd international workshop on social data on the Web. Hungary:CEUR-WS,2010:595-608.
[5] 叶光辉,李纲.社会语义网络结构分析——以MetaFilter为例[J].情报理论与实践,2015,38(12):57-63.
[6] 李勇军.在线社交网络影响力分析[J].复杂系统与复杂性科学,2012,9(3):22-37.
[7] 吴信东,李毅,李磊.在线社交网络影响力分析[J].计算机学报,2014,37(4):735-752.
[8] 王晓鸥.结合时间因子的社交网络用户影响力分析[D].广州:广东工业大学,2015.
[9] MISLOVE A, KOPPULA H S, GUMMADI K P, et al.Growth of the flickr social network[C]// Proceedings of the 1st ACM SIGCOMMWorkshop on social networks.New York: ACM Press, 2008: 25-30.
[10] 郭碧坚,韩宇.同行评议制:方法,理论,功能,指标[J].科学学研究,1994(3):63-73.
[11] 林鸿飞,王健,熊大平,等.基于类别参与度的社区问答专家发现方法[J].计算机工程与设计,2014,35(1):333-338.
[12] 史玉珍,彭智勇.基于修正h指数的学科领域专家发现的研究[J].计算机工程与应用, 2011,47(29):1-3.
[13] 刘健,李绮,刘宝宏,等.基于话题模型的专家发现方法[J]. 国防科技大学学报,2013, 35(2):127-131.
[14] 李纲,叶光辉,张岩."小众专家"特征识别——基于MetaFilter的实证分析[J].现代图书情报技术,2015(6):71-77.
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