基于社交网络的社交行为分析

doi:10.11999/JEIT161273

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Abstract Recently, social network applications develop dramatically. Social network related social behaviors are one of the most important areas, which receive broadly attentions from researchers in academics. This survey paper analyzes the social behaviors comprehensively with respect to the causes of social behaviors, the performance of social behaviors and the influence of social behaviors. More specifically, after analyzing the basic concepts of behaviors in social networks, the three most important causes of behaviors in social networks are firstly introduced, such as user adoption, user loyalty and user trust. With these causes, the performance of user behaviors in social networks can be analyzed with respect to three common behaviors, including general usage behaviors, content creation behaviors and content consumption behaviors. Finally, the research on the influence of social network behaviors is presented, which includes the most important aspects, such as influence evaluation and behavior induction. The systematical analysis of social behaviors points out the future directions of related research in next steps.

Key words： User behaviors Social behaviors Behavior modeling Cause of behaviors Performance of behaviors Influence of behaviors

Received: 24 November 2016 Published: 14 June 2017

PACS:

TP393

Fund:The National 973 Program of China (2013CB329604), The National Key Research and Development Program of China (2016YFB1000901), The National Natural Science Foundation of China (61503114)

Corresponding Authors: LI Lei E-mail: lilei@hfut.edu.cn

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	LI Lei
	WANG Meng
	WU Xindong

Cite this article:

LI Lei,WANG Meng,WU Xindong. Social Network Based Social Behavior Analysis[J]. JEIT, 2017, 39(9): 2108-2118.

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http://jeit.ie.ac.cn/EN/10.11999/JEIT161273 OR http://jeit.ie.ac.cn/EN/Y2017/V39/I9/2108

[1]	GOYAL A, BONCHI F, and LAKSHMANAN L V S. Learning influence probabilities in social networks[C]. Proceedings of the third ACM international conference on Web search and data mining, New York, NY, USA, 2010: 241-250. doi: 10.1145/1718487.1718518.
[2]	FANG B, XU J, LI J, et al. Online social network analysis[J]. Publishing House of Electronics Industry, 2015, 30(2): 187-199.
[3]	NEWMAN M E J. Networks: An Introduction[M]. Oxford, UK, Oxford University, 2010: 1-784.
[4]	陈季梦, 陈佳俊, 刘杰, 等. 基于结构相似度的大规模社交网络聚类算法[J]. 电子与信息学报, 2015, 37(2): 449-454. doi: 10.11999/JEIT140512.
	CHEN Jimeng, CHEN Jiajun, LIU Jie, et al. Clustering algorithms for large-scale social networks based on structural similarity[J]. Journal of Electronics & Information Technology, 2015, 37(2): 449-454. doi: 10.11999/JEIT140512.
[5]	刘世超, 朱福喜, 甘琳. 基于标签传播概率的重叠社区发现算法[J]. 计算机学报, 2016, 39(4): 717-729. doi: 10.11897/ SP.J.1016.2016.00717.
	LIU Shichao, ZHU Fuxi, and GAN Lin. A label-propagation- probability-based algorithm for overlapping community detection[J]. Chinese Journal of Computers, 2016, 39(4): 717-729. doi: 10.11897/SP.J.1016.2016.00717.
[6]	罗恩韬, 王国军. 移动社交网络中一种朋友发现的隐私安全保护策略[J]. 电子与信息学报, 2016, 38(9): 2165-2172. doi: 10.11999/JEIT151479.
	LUO Entao and WANG Guojun. A novel friends matching privacy preserving strategy in mobile social networks[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2165-2172. doi: 10.11999/JEIT151479.
[7]	张少波, BHUIYAN Z A, 刘琴, 等. 移动社交网络中基于代理转发机制的轨迹隐私保护方法[J]. 电子与信息学报, 2016, 38(9): 2158-2164. doi: 10.11999/JEIT151136.
	ZHANG Shaobo, BHUIYAN Z A, LIU Qin, et al. The method of trajectory privacy preserving based on agent forwarding mechanism in mobile social networks[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2158-2164. doi: 10.11999/JEIT151136.
[8]	谢柏林, 蒋盛益, 周咏梅, 等. 基于把关人行为的微博虚假信息及早检测方法[J]. 计算机学报, 2016, 39(4): 730-744. doi: 10.11897/SP.J.1016.2016.00730.
	XIE Bailin, JIANG Shengyi, ZHOU Yongmei, et al. Misinformation detection based on gatekeepers' behaviors in microblog[J]. Chinese Journal of Computers, 2016, 39(4): 730-744. doi: 10.11897/SP.J.1016.2016.00730.
[9]	张玉清, 吕少卿, 范丹. 在线社交网络中异常帐号检测方法研究[J]. 计算机学报, 2015, 38(10): 2011-2027. doi: 10.11897/ SP.J.1016.2015.02011.
	ZHANG Yuqing, LÜ Shaoqing, and FAN Dan. Anomaly detection in online social networks[J]. Chinese Journal of Computers, 2015, 38(10): 2011-2027. doi: 10.11897/SP.J. 1016.2015.02011.
[10]	MAIA M, ALMEIDA J, and ALMEIDA V. Identifying user behavior in online social networks[C]. Proceedings of the 1st Workshop on Social Network Systems, Glasgow, Scotland, UK, 2008: 1-6. doi: 10.1145/1435497.1435498.
[11]	张锡哲, 吕天阳, 张斌. 基于服务交互行为的复杂服务协同网络建模[J]. 软件学报, 2016, 27(2): 231-246. doi: 10.13328 /j.cnki.jos.004847.
	ZHANG Xizhe, LU Tianyang, and ZHANG Bin. Modeling complex collaboration network for service-oriented software based on execution behaviors[J]. Journal of Software, 2016, 27(2): 231-246. doi: 10.13328/j.cnki.jos.004847.
[12]	KWON O and WEN Y. An empirical study of the factors affecting social network service use[J]. Computers in Human Behavior, 2010, 26(2): 254-263. doi: 10.1016/j.chb.2009.04. 011.
[13]	NIKOU S and BOUWMA H. Ubiquitous use of mobile social network services[J]. Telematics and Informatics, 2014, 31(3): 422-433. doi: 10.1016/j.tele.2013.11.002.
[14]	SLEDGIANOWSKI D and KULVIWAT S. Social network sites: Antecedents of user adoption and usage[C]. Proceedings of the 14th Americas Conference on Information Systems, Toronto, 2008: 83-93. doi: 10.4018/jantti.2010040104.
[15]	WU Y C J, SHEN J P, and CHANG C L, Electronic service quality of Facebook social commerce and collaborative learning[J]. Computers in Human Behavior, 2015, 51(B), 1395-1402. doi: 10.1016/j.chb.2014.10.001.
[16]	BAKER R K and WHITE K M. Predicting adolescents’ use of social networking sites from an extended theory of planned behaviour perspective[J]. Computers in Human Behavior, 2010, 26(6): 1591-1597. doi: 10.1016/j.chb.2010.06.006.
[17]	PELLING E L and WHITEK M. The theory of planned behavior applied to young people’s use of social networking web sites[J]. CyberPsychology & Behavior, 2009, 12(6): 755-759. doi: 10.1089/cpb.2009.0109.
[18]	CHANG Y P and ZHU D H. Understanding social networking sites adoption in China: A comparison of pre-adoption and post-adoption[J]. Computers in Human Behavior, 2011, 27(5): 1840-1848. doi: 10.1016/j.chb.2011.04. 006.
[19]	YAZDANPANAH M and FOROUZANI M. Application of the theory of planned behaviour to predict Iranian students' intention to purchase organic food[J]. Journal of Cleaner Production, 2015, 107: 342-352. doi: 10.1016/j.jclepro.2015. 02.071.
[20]	KANG Y S, HONG S, and LEE H. Exploring continued online service usage behavior: The roles of self-image congruity and regret[J]. Computers in Human Behavior, 2009, 25(1): 111-122. doi: 10.1016/j.chb.2008.07.009.
[21]	YAO C and SHAO P. An empirical research of social network sites continuance: Based on a modified expectation- confirmation model[J]. China Journal of Information Systems, 2011, 8(1): 23-33.
[22]	SHIN S and HALL D J. Identifying factors affecting SNS users as a temporary or persistent user: An empirical study [C]. Proceedings of the Seventeenth Americas Conference on Information Systems, Detroit, Michigan, USA, 2011: 316-417.
[23]	ZHANG H, LU Y, GUPTA S, et al. Understanding group- buying websites continuance-an extension of expectation confirmation model[J]. Internet Research, 2015, 25(5): 767-793. doi: 10.1108/IntR-05-2014-0127.
[24]	ZHOU T, LI H, and LIU Y. The effect of flow experience on mobile SNS users’ loyalty[J]. Industrial Management & Data Systems, 2010, 110(6): 930-946. doi: 10.1108/026355710110 5126.
[25]	HSU C L and WU C. Understanding users’ continuance of Facebook: An integrated model with the unified theory of acceptance and use of technology, expectation disconfirmation model, and flow theory[J]. International Journal of Virtual Communities and Social Networking, 2011, 3(2): 1-16. doi: 10.4018/jvcsn.2011040101.
[26]	WU Y, WANG Z, CHANG K, et al. Why people stick to play social network site based entertainment applications: Design factors and flow theory perspective[C]. Pacific Asia Conference on Information Systems, Taipe, 2010: 1041-1050.
[27]	CHANG C C. Examining users’ intention to continue using social network games: A flow experience perspective[J]. Telematics and Informatics, 2013, 30(4): 311-321. doi: 10.1016/j.tele.2012.10.006.
[28]	HUANG C H, HSU M C, and CHANG H M. An exploratory study of social game by flow theory and social network theory [C]. International Conference on Computer Science and Intelligent Communication (CSIC 2015), 2015: 418-421.
[29]	韩祺祎, 任梦吟, 文红. 基于拓扑势的P2P社区推荐信任模型[J]. 电子与信息学报, 2015, 37(6): 1279-1284. doi: 10.11999/ JEIT141303.
	HAN Qiyi, REN Mengyin, and WEN Hong. Topological potential based recommendation trust model for P2P communities system[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1279-1284. doi: 10.11999/JEIT 141303.
[30]	KRAMER R M. Trust and distrust in organizations: Emerging perspectives, enduring questions[J]. Annual Review of Psychology, 1999, 50: 569-598. doi: 10.1146/annurev. psych.50.1.569.
[31]	LI L and WANG Y. The roadmap of trust and trust evaluation in Web applications and Web services[J]. Advanced Web Services, 2014: 75-99. doi: 10.1007/978-1- 4614-7535-4_4.
[32]	LI L, WANG Y, LIU G, et al. Context-aware reviewer assignment for trust enhanced peer review[J]. PLoS ONE, 2015, 10(6). e0130493. doi: 10.1371/journal.pone.0130493.
[33]	BOON S D and HOLMES J G. The Dynamics of Interpersonal Trust: Resolving Uncertainty in the Face of Risk[M]. Cambridge UK: Cambridge University, 1991: 167-182.
[34]	BREWER M B. In-group Favoritism: The Subtle Side of Intergroup Discrimination[M]. New York, USA, Russell Sage Found, 1996: 160-171.
[35]	MARCH J G. A Primer on Decision Making: How decisions Happen[M]. New York, USA, Free Press, 2009: 1-289.
[36]	GOLBECK J and HENDLER J. Accuracy of metrics for inferring trust and reputation in semantic Web-based social networks[C]. Proceedings of 14th International Conference on Knowledge Engineering and Knowledge Management, 2004: 116-131. doi: 10.1007/978-3-540-30202-5_8.
[37]	GOLBECK J and HENDLER J. Inferring trust relationships in web-based social networks[J]. ACM Transactions on Internet Technology, 2006, 6(4): 497-529. doi: 10.1145/ 1183463.183470.
[38]	GUHA R, KUMAR R, RAGHAVAN P, et al. Propagation of trust and distrust[C]. Proceedings of the 13th International Conference on World Wide Web, New York, NY, USA, 2004: 403-412. doi: 10.1145/988672.988727.
[39]	WALTER F, BATTISTON S, and SCHWEITZER F. A model of a trust-based recommendation system on a social network[J]. AAMAS Journal, 2008, 16(1): 57-74. doi: 10. 1007/s10458-007-9021-x.
[40]	JAMAIL M and ESTER M. Trustwalker: A random walk model for combining trust-based and item-based recommendation[C]. Proceedings of the 15th International Conference on Knowledge Discovery and Data Mining, Paris, France, 2009: 397-406. doi: 10.1145/1557019.1557067.
[41]	GOLDER S A, WILKINSON D M, and HUBERMAN B A. Rhythms of Social Interaction: Messaging within a Massive Online Network/Communities and Technologies[M]. London: Communities and Technologies, 2007: 41-66.
[42]	GYARMATI L and TRINH T A. Measuring user behavior in online social networks[J]. IEEE Network, 2010, 24(5): 26-31. doi: 10.1109/MNET.2010.5578915.
[43]	WANG Y C, BURKE M, and KRAUT R E. Gender, topic, and audience response: An analysis of user-generated content on facebook[C]. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France, 2013: 31-34.
[44]	QIU L, LIN H, RAMSAY J, et al. You are what you tweet: Personality expression and perception on twitter[J]. Journal of Research in Personality, 2012, 46(6): 710-718. doi: 10.1016 /j.jrp.2012.08.008.
[45]	BOYLE K and JOHNSON T J. MySpace is your space? Examining self-presentation of MySpace users[J]. Computers in Human Behavior, 2010, 26(6): 1392-1399. doi: 10.1016/ j.chb.2010.04.015.
[46]	TIFFERET S and VILNAI I. Gender differences in Facebook self-presentation: An international randomized study[J]. Computers in Human Behavior, 2014, 35(6): 388-399. doi: 10.1016/j.chb.2014.03.016.
[47]	ZWOL R V. Flickr: Who is looking?[C]. Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, Fremont, CA, 2007: 184-190. doi: 10.1109/WI. 2007.22
[48]	MORRIS M R, TEEVAN J, and PANOVICH K. What do people ask their social networks, and why?: A survey study of status message q&a behavior[C]. Proceedings of the SIGCHI conference on Human factors in computing systems, Cambridge, MA, USA, 2010: 1739-1748. doi: 10.1145/ 1753326.1753587.
[49]	SHEN H, LIU G, WANG H, et al. SocialQ&A: An online social network based question and answer system[J]. IEEE Transactions on Big Data, 2017, 3(1): 91-106. doi: 10.1109 /TBDATA.2016.2629487.
[50]	高全力, 高岭, 杨建锋, 等. 上下文感知推荐系统中基于用户认知行为的偏好获取方法[J]. 计算机学报, 2015, 38(9): 1767-1776. doi: 10.11897/SP.J.1016.2015.01767.
	GAO Quanli, GAO Ling, YANG Jianfeng, et al. A preference elicitation method based on users, cognitive behavior for context-aware recommender system[J]. Chinese Journal of Computers, 2015, 38(9): 1767-1776. doi: 10.11897/ SP.J.1016. 2015.01767.
[51]	王晨旭, 管晓宏, 秦涛, 等. 微博消息传播中意见领袖影响力建模研究[J]. 软件学报, 2015, 26(6): 1473-1485. doi: 10.13328 /j.cnki.jos.004627.
	WANG Chenxu, GUAN Xiaohong, QIN Tao, et al. Modeling on opinion leader,s influence in microblog message propagation and its application[J]. Journal of Software, 2015, 26(6): 1473-1485. doi: 10.13328/j.cnki.jos.004627.
[52]	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. doi: 10.3724/SP.J.1016.2014.00735.
	WU Xindong, LI Yi, and LI Lei. Influence analysis of online social networks[J]. Chinese Journal of Computers, 2014, 37(4): 735-752. doi: 10.3724/SP.J.1016.2014.00735.
[53]	许宇光, 潘惊治, 谢惠扬. 基于最小点覆盖和反馈点集的社交网络影响最大化算法[J]. 电子与信息学报, 2016, 38(4): 795-802. doi: 10.11999/JEIT160019.
	XU Yuguang, PAN Jingzhi, and XIE Huiyang. Minimum vertex covering and feedback vertex set-based algorithm for influence maximization in social network[J]. Journal of Electronics & Information Technology, 2016, 38(4): 795-802. doi: 10.11999/JEIT160019.
[54]	ROMERO D M, GALUBA W, ASUR S, et al. Influence and passivity in social media[J]. Ssrn Electronic Journal, 2010, 6913(1): 18-33. doi: 10.1007/978-3-642-23808-6_2.
[55]	LI L, HE J, WANG M, et al. Trust agent-based behavior induction in social networks[J]. IEEE Intelligent Systems, 2016, 30(1): 31-55. doi: 10.1109/MIS.2016.6.
[56]	刘宇, 吴斌, 曾雪琳, 等. 一种基于社交网络社区的组推荐框架[J]. 电子与信息学报, 2016, 38(9): 2150-2157. doi: 10.11999 /JEIT160544.
	LIU Yu, WU Bin, ZENG Xuelin, et al. A group recommendation framework based on social network community[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2150-2157. doi: 10.11999/JEIT 160544.
[57]	王元卓, 于建业, 邱雯, 等. 网络群体行为的演化博弈模型与分析方法[J]. 计算机学报, 2015, 38(2): 282-300. doi: 10.3724 /SP.J.1016.2015.00282.
	WANG Yuanzhuo, YU Jianye, QIU Wen, et al. Evolutionary game model and analysis methods for network group behavior[J]. Chinese Journal of Computers, 2015, 38(2): 282-300. doi: 10.3724/SP.J.1016.2015.00282.
[58]	刘玮, 贺敏, 王丽宏, 等. 基于用户行为特征的微博转发预测研究[J]. 计算机学报, 2016, 39(10): 1992-2006. doi: 10.11897 /SP.J.1016.2016.01992.
	LIU Wei, HE Min, WANG Lihong, et al. Research on microblog retweeting prediction based on user behavior features[J]. Chinese Journal of Computers, 2016, 39(10): 1992-2006. doi: 10.11897/SP.J.1016.2016.01992.
[59]	邢千里, 刘列, 刘奕群, 等. 微博中用户标签的研究[J]. 软件学报, 2015, 26(7): 1626-1637. doi: 10.13328/j.cnki.jos.004655.
	XING Qianli, LIU Lie, LIU Yiqun, et al. Study on user tags in Weibo[J]. Journal of Software, 2015, 26(7): 1626-1637. doi: 10.13328/j.cnki.jos.004655.
[60]	李慧嘉, 李慧颖, 李爱华. 多尺度的社团结构稳定性分析[J].计算机学报, 2015, 38(2): 301-312. doi: 10.3724/SP.J.1016. 2015.00301.
	LI Huijia, LI Huiying, and LI Aihua. Analysis of multi-scale stability in community structure[J]. Chinese Journal of Computers, 2015, 38(2): 301-312. doi: 10.3724/SP.J.1016. 2015.00301.