高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于社会系统响应函数的在线群体分类研究

刘嘉琪,  齐佳音

downloadPDF
文章导航 > 电子与信息学报  > 2016 >  38(9): 2141-2149
刘嘉琪, 齐佳音. 基于社会系统响应函数的在线群体分类研究[J]. 电子与信息学报, 2016, 38(9): 2141-2149. doi: 10.11999/JEIT160515
引用本文: 刘嘉琪, 齐佳音. 基于社会系统响应函数的在线群体分类研究[J]. 电子与信息学报, 2016, 38(9): 2141-2149. doi: 10.11999/JEIT160515
shu
LIU Jiaqi, QI Jiayin. Research on Online Group Classification Based on the Response Function of Social System[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2141-2149. doi: 10.11999/JEIT160515
Citation: LIU Jiaqi, QI Jiayin. Research on Online Group Classification Based on the Response Function of Social System[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2141-2149. doi: 10.11999/JEIT160515
shu

基于社会系统响应函数的在线群体分类研究

doi: 10.11999/JEIT160515
  • 1.

    (北京邮电大学经济管理学院 北京 100876) ②(北京邮电大学可信分布式计算与服务教育部重点实验室 北京 100876) ③(上海对外经贸大学工商管理学院 上海 201620)

基金项目: 

国家973基础重大课题(SQ2012CB037347)，国家自然科学基金(71231002)

Research on Online Group Classification Based on the Response Function of Social System

  • 1.

    (Institute of Economic Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Funds: 

The Major State Basic Research Development Program of China (973 Program)(SQ2012CB037347), The National Natural Science Foundation of China (71231002)

    摘要
  • 摘要: 该文致力于丰富在线群体的研究体系，为未来探索深层次科学问题提供支撑。讨论了在线群体与在线话题的定义及常见分类方式。重点展现了一种全新的依据观测社会系统响应函数的趋势将在线话题分为4类的定性研究方法，即外源性首要传播型话题、外源性次要传播型话题、内源性首要传播型话题和内源性次要传播型话题，并且进一步以此区分讨论不同类型话题的在线群体。同时，明确地提出了规范的使用步骤与实际操作时可能遇到的问题及解决方法。最后尝试运用该方法来估计以新浪微博与百度贴吧为代表的在线社交网络平台中各类话题群体的分布情况。
    Abstract: Devoted to enriching the research system of online group, and laying the foundation for exploring deep scientific problem in the future, this paper discusses the definition of online group, online topic, common classification methods, and primarily introduces a new qualitative method of online topic classification based on observing the trend of a social system response function. Through this method, online topic discussed by online group can be divided into exogenous critical topic, exogenous subcritical topic, endogenous critical topic, and endogenous subcritical topic. The standardized steps to this method are put forward, and it is figured out that the problems may occur when applying it to the practice. Whats more, this method is tried to estimate the distribution of four types of topics in the two representatives of online social network platform Sina microblog and Baidu Tieba.
    • HTML全文
    • 参考文献(45)
  • BON Gustave Le. The Crowd: A Study of The Popular Mind[M]. New York: The Macmillan Co., 1896: 11-43.
    ARMSTRONG A and HAGELIII J H. The real value of online communities[J]. Harvard Business Review, 1996, 74(3): 85-95. doi: 10.12691/ijefm-2-2-2.
    曹玖新, 陈高君, 吴江林, 等. 基于多维特征分析的社交网络意见领袖挖掘[J]. 电子学报, 2016, 44(4): 898-905. doi: 10. 3969/j.issn.0372-2112.2016.04.021.
    CAO Jiuxin, CHEN Gaojun, WU Jianglin, et al. Multi- feature based opinion leader mining in social networks[J]. Acta Electronica Sinica, 2016, 44(4): 898-905. doi: 10.3969/ j.issn.0372-2112.2016.04.021.
    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(4): 735-752.
    WU Xindong, LI Yi, and LI Lei. Influence analysis of online social networks[J]. Chinese Journal of Computers, 2014(4): 735-752.
    李东方, 俞能海, 尹华罡. 一种Web 2.0环境下互联网热点挖掘算法[J]. 电子与信息学报, 2010, 32(5): 1141-1145. doi: 10. 3724/SP.J.1146.2009.00641.
    LI Dongfang, YU Nenghai, and YIN Huagang. Mining hot topic on Internet under web 2.0[J]. Journal of Electronics Information Technology, 2010, 32(5): 1141-1145. doi: 10. 3724 /SP.J.1146.2009.00641.
    ZHAO L, LI Y, LIU X, et al. A graph-based bursty topic detection approach in user-generated texts[C]. IEEE Web Information System and Application Conference, Tianjin, China, 2015: 273-278. doi: 10.1109/WISA.2014.57.
    ZHANG C, WANG H, CAO L, et al. A hybrid term-term relations analysis approach for topic detection[J]. Knowledge-based Systems, 2015, 93(11): 109-120. doi: 10.1016/j.knosys.2015.11.006.
    刘权, 郭武. 基于核主成分分析的话题跟踪系统[J]. 清华大学学报: 自然科学版, 2013(6): 865-868.
    LIU Quan and GUO Wu. Topic tracking system based on kernel principal component analysis[J]. Journal of Tsinghua University: Natural Science Edition, 2013(6): 865-868.
    谢丽星, 周明, 孙茂松. 基于层次结构的多策略中文微博情感分析和特征抽取[J]. 中文信息学报, 2012, 26(1): 73-83.
    XIE Lixing, ZHOU Ming, and SUN Maosong. Sentiment analysis and feature extraction of Chinese micro-blog based on hierarchical structure[J]. Journal of Chinese Information Processing, 2012, 26(1): 73-83.
    REN Yafeng, WANG Ruimin, and JI Donghong. A topic- enhanced word embedding for twitter sentiment classification [J]. Information Sciences, 2016, 24(7): 1031-1040. doi: 10. 1016/j.ins.2016.06.040.
    刘玉新. Web2.0互联网在线话题发现和热度评估[D]. [硕士论文], 华南理工大学, 2013: 23-45.
    LIU Yuxin. Web2.0 Internet online topic discovery and hotness evaluation[D]. [Master dissertation], South China University of Technology, 2013: 23-45.
    龙志祎, 程葳, 沈俊辉. TDT中新发现话题的分类研究与实现[J]. 武汉理工大学学报: 信息与管理工程版, 2009, 5(5): 762-765.
    LONG Zhiyi, CHEN Wei, and SHEN Junhui. Research and implementation of new detected topic classification in TDT technology[J]. Journal of Wuhan University: Information Management Engineering, 2009, 5(5): 762-765.
    刘宝忠. 微博客在线社会网络的特性研究[D]. [硕士论文], 西安理工大学, 2011: 32-35.
    LIU Baozhong. The research on the characteristics of microblog[D]. [Master dissertation], Xi,an University of Technology, 2011: 32-35.
    张永军, 刘金岭, 马甲林. 中文短信文本信息流中多话题的分类抽取[J]. 现代图书情报技术, 2014, 30(Z1): 101-106.
    ZHANG Yongjun, LIU Jinling, and MA Jialin. Classification of multi topic extraction based on Chinese short information text message flow[J]. New Technology of Library and Information Service, 2014, 30(Z1): 101-106.
    易欣. 微话题的社会语言学解读[J]. 北方文学旬刊, 2013(6): 143-145.
    YI Xin. A sociolinguistic interpretation of the micro topic[J]. Northern Literature Magazine, 2013(6): 143-145.
    张萌. 关于新浪微博热门话题的分析研究[D]. [硕士论文], 山东大学, 2015: 11-24.
    ZHANG Meng. The analysis of the hot topics on Sina microblog[D]. [Master dissertation], Shandong University, 2015: 11-24.
    洪宇, 张宇, 刘挺, 等. 话题检测与跟踪的评测及研究综述[J]. 中文信息学报, 2007, 21(6): 71-87. doi: 10.3969/j.issn.1003- 0077.2007.06.011.
    HONG Yu, ZHANG Yu, LIU Ting, et al. Review on the evaluation and research of topic detection and tracking[J]. Journal of Chinese Information Processing, 2007, 21(6): 71-87. doi: 10.3969/j.issn.1003-0077.2007.06.011.
    ELLISON N B. Social network sites: Definition, history, and scholarship[J]. Journal of Computer-mediated Communication, 2007, 13(1): 210-230. doi: 10.111/j.1083- 6101.2007.00393x.
    SPROULL L. Online Communities[M]. New York: Handbook of Computer Networks: Distributed Networks, Network Planning, Control, Management, and New Trends and Applications, 2012: 898-914. doi: 10.1002/047148296X. tie128.
    ALDRICH H E and RUEF M. Organizations Evolving[M]. London: SAGE Publications Ltd, 2006: 121-123. doi: 10. 4135/9781446212509.
    MATZAT U. A theory of relational signals in online groups [J]. New Media Society, 2009, 11(3): 375-394. doi: 10.1177/ 1461444808101617.
    SORNETTE D, DESCHATRES F, GILBERT T, et al. Endogenous versus exogenous shocks in complex networks:an empirical test using book sale rankings[J]. Physical Review Letters, 2004, 93(22): 211-218. doi: 10.1103/PhysRevLett. 93.228701.
    CRANE R. Robust dynamic classes revealed by measuring the response function of a social system[J]. Proceedings of the National Academy of Sciences, 2008, 105(41): 15649-15653. doi: 10.1073/pnas.0803685105.
    KWAK H, LEE C, PARK H, et al. What is twitter, a social network or a news media?[C]. the 19th International World Wide Web (WWW) Conference, Raleigh, NC, USA, 2010: 591-600.
    许小东. 管理者工作内源压力与外源压力的结构模型研究[J]. 管理工程学报, 2007, 21(1): 3-40.
    XU Xiaodong. A structure modeling study on the job intrinsic stressors and extrinsic stressors of the managers[J]. Journal of Industrial Engineering and Engineering Management, 2007, 21(1): 3-40.
    POSNER M I. Orienting of attention[J]. Quarterly Journal of Experimental Psychology, 2007, 32(1): 3-25.
    宋恩梅, 左慧慧. 新浪微博中的权威与人气: 以社会网络分析为方法[J]. 图书情报知识, 2012(3): 43-54.
    SONG Enmei and ZUO Huihui. Authority and popularity in micro-blog Sina: A social network analysis method[J]. Documentation, Information Knowledge, 2012(3): 43-54.
    李珊珊. 百度贴吧10周年, 为兴趣而生关于贴吧十年粉丝文化变迁的解读[J]. 新闻世界, 2014(10): 202-204.
    LI Shanshan. Baidu Tieba 10 anniversary, for the interest and life-on the BBS ten years fans cultural changes[J]. News World, 2014(10): 202-204.
    路双. 浅析网络趣缘群体的特征以百度贴吧爆料贴为例[J]. 新闻世界, 2015(3): 47-48.
    LU Shuang. Analysis of the characteristics of the network interest margin group-Baidu Tieba posted as an example[J]. News World, 2015(3): 47-48.
    • 相关文章
    • 施引文献
  • 资源附件(0)
  • 加载中
计量
  • 文章访问数:  1336
  • HTML全文浏览量:  91
  • PDF下载量:  603
  • 被引次数: 0
出版历程
  • 收稿日期:  2016-05-23
  • 修回日期:  2016-07-22
  • 刊出日期:  2016-09-19

目录

    /

    返回文章
    返回

    Copyright © 2018《电子与信息学报》编辑部 京ICP备20021838号-8

    中国科学院电子学研究所,北京市2702信箱,邮编：100190

    电话：010-58887066传真：021-64253812Email：jeit@mail.ie.ac.cn

    本系统由 北京仁和汇智信息技术有限公司 开发    百度统计