融合多源数据的微信用户信息分享行为特征研究
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摘要
【目的/意义】在于探索微信用户分享行为时空特征,为揭示用户间信息分享轨迹和社交网络结构的演化规律提供借鉴。【方法/过程】由于微信对线上数据技术采集的限制,已有的研究多集中以访谈和问卷调查的方式,对分析用户行为规律和行为特征具有很大的局限性。为了解决这一问题,本文融合多源数据采集与分析技术,实现了247711条微信用户分享数据的特征提取。【结果/结论】微信用户对微信具有较高的依赖度,分享与阅读之间的间隔时间分布具有强阵发性,而且微信中分享内容被转发的路径长度远远高于以微博为代表的综合类社交应用。
【Purpose/significance】To explore the temporal and spatial features of WeChat users' sharing behavior, so as to reveal sharing information tracks among users and evolution regularities of social network structure.【Method/process】Due to the technology restriction on data acquisition by WeChat, most of the existing researches focused on interviews and ques-tionnaires, which had great limitations in analyzing user behavior rules and behavior characteristics. In order to solve thisproblem, this paper used the data acquisition and analysis technology to realize the feature extraction of 247711 WeChat users.【Result/conclusion】The results show that WeChat users were highly dependent on WeChat in their daily life, and theinterval time distribution between sharing users and reading users was with strongly temporal burst. Additionally, we foundthat the average path length of information shared in WeChat was much higher than that in micro-blogging.
【Purpose/significance】To explore the temporal and spatial features of WeChat users' sharing behavior, so as to reveal sharing information tracks among users and evolution regularities of social network structure.【Method/process】Due to the technology restriction on data acquisition by WeChat, most of the existing researches focused on interviews and ques-tionnaires, which had great limitations in analyzing user behavior rules and behavior characteristics. In order to solve thisproblem, this paper used the data acquisition and analysis technology to realize the feature extraction of 247711 WeChat users.【Result/conclusion】The results show that WeChat users were highly dependent on WeChat in their daily life, and theinterval time distribution between sharing users and reading users was with strongly temporal burst. Additionally, we foundthat the average path length of information shared in WeChat was much higher than that in micro-blogging.
引文
1中国互联网络信息中心.2015年中国社交应用用户行为研究报告[R].2016.04. http://research.cnnic.cn/
2 赵文晶,申利净.社交媒体用户迁移背景下微博、微信的态度传播生态研究[J].中国软科学,2015,(10):60-69.
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4 Chen L., Chin F. G., Sun Y., Amran R. Integrating guanxi into technology acceptance:An empirical investigation of WeChat[J].Telematics and Informatics,2017,34(7):1125-1142.
5 Gan C.M.Understanding WeChat users’liking behavior:An empirical study in China[J]. Computers in Human Behavior, 2017,(68):30-39.
6 于玲玲,周密,赵西萍,刘倩.移动社交网络用户内容创造与分享行为研究——社会网络与自恋的交互效应[J].情报学报,2016,(9):1000-1008.
7 Tong S., Van Der Heide B., Langwell L.,&Walther,J.Too much of a good thing? The relationship between number of friends and interpersonal impression on Facebook[J]. Journal of Computer-Mediated Communication, 2008,13(3):531-549.
8 yan R. M., Deci E. L. Intrinsic and extrinsic motivations:Classic definitions and new directions[J]. Contemporary Educational Psychology,2000,25(1):54-67.
9 Ruggiero T.E. Uses and gratification theory in the21 st century[J]. Mass Communication&Society,2000,3(1):3-37.
10 Park N., Kee K.F., Valenzuela S.Being immersed in social networking environment:Facebook groups, uses and gratifications, and social outcomes[J]. CyberPsychology&Behavior, 2009,12(6):729-733.
11 Leung L.Generational differences in content generation in social media:The roles of the gratifications sought and of narcissism[J]. Computers in Human Behavior,2013, 29(3)997-1006.
12 赵英,范娇颖.大学生持续使用社交媒体的影响因素对比研究——以微信、微博和人人网为例[J].情报杂志,2016,35(1):188-195.
13 黄炜,余辉,李岳峰.基于微信用户行为的分享预测模型研究[J].情报理论与实践,2016,39(11):89-94.
14 杨海娟.微信环境下用户适应性信息分享行为影响因素研究——基于规范性压力和社交价值的“推—拉”视角[J].情报科学,2017,35(8):134-140.
15 Barabási A. The origin of bursts and heavy tails in human dynamics[J]. Nature,2005,435(7039):207-211.
16 Ghoshal G, Holme P. Attractiveness and activity in Internet communities[J]. Physica A, 2006,(364):603-609.
17 Yan Q., Wu L., Zheng L. Social network based microblog user behavior analysis[J]. Physica A, 2013, 392(7):1712-1723.
18 Wang C., Guan X., Qin T., et al. Modeling the heterogeneity of human dynamics based on the measurements of influential users in Sina Microblog[J]. Physica A:Statistical Mechanics and its Applications,2015,(428):239-249.
19 辛文娟,赖涵.群体极化视域下网络舆情的演化机制研究——以微博网民讨论“浙江温岭杀医案”为例[J].情报杂志,2015,(2):47-52.
20 Ou C.G., Jin X.L.,Wang Y.Z., Cheng X.Q. Modelling heterogeneous information spreading abilities of social network ties[J].Simulation Modelling Practice and Theory,2017,(75):67-76.
21 Ball B., Newman M. E. Friendship networks and social status[J].Network Science, 2013, 1(1):16-30.
22 Livan G., Caccioli F., Aste T.Excess reciprocity distorts reputation in online social networks[J].Scientific Report, 2017,(7):3551.
23 Pfeil U., Arjan R.,&Zaphiris P. Age differences in online social networking—A study of user profiles and the social capital divide among teenagers and older users in MySpace[J]. Computers in Human Behavior, 2009,(25):643-654.
24 Hargittai E. Whose space? Differences Among Users and Non-Users of Social Network Sites[J]. Journal of Computer-Mediated Communication, 2008,(13):276-297.
25 Wijesundara T. R..Motivations and usage patterns of social networking sites:Exploring cultural differences between United States&Sri Lanka[J]. Canadian Social Science,2015,(10):176-185.
26 Wang J. L., Jackson L. A., Zhang D. J., et al. The relationships among the Big Five Personality factors, self-esteem,narcissism, and sensation-seeking to Chinese University students’uses of social networking sites(SNSs)[J]. Computers in Human Behavior, 2012, 28(6):2313-2319.
27 Hollenbaugh E. E., and Ferris A. L. Facebook self-disclosure:Examining the role of traits, social cohesion, and motives[J]. Computers in Human Behavior, 2014, 30(1):50-58.
28 顾东晓,孙建军,张悦,盛东方,杨苏.基于计划行为理论的用户链接分享研究[J].运筹与管理,2016,25(2):173-179.
29 皇甫军.科研社交网络平台功能因素和用户行为的相关性分析[J].情报科学,2017,35(8):62-67.
30 Goh K.I., Barabási A. L. Burstiness and memory in complex systems[J]. Europhys Lett, 2008, 81(4):48002.
2 赵文晶,申利净.社交媒体用户迁移背景下微博、微信的态度传播生态研究[J].中国软科学,2015,(10):60-69.
3 熊茵,赵振宇.微信舆情的传播特征及风险探析[J].现代传播,2016,(2):79-82.
4 Chen L., Chin F. G., Sun Y., Amran R. Integrating guanxi into technology acceptance:An empirical investigation of WeChat[J].Telematics and Informatics,2017,34(7):1125-1142.
5 Gan C.M.Understanding WeChat users’liking behavior:An empirical study in China[J]. Computers in Human Behavior, 2017,(68):30-39.
6 于玲玲,周密,赵西萍,刘倩.移动社交网络用户内容创造与分享行为研究——社会网络与自恋的交互效应[J].情报学报,2016,(9):1000-1008.
7 Tong S., Van Der Heide B., Langwell L.,&Walther,J.Too much of a good thing? The relationship between number of friends and interpersonal impression on Facebook[J]. Journal of Computer-Mediated Communication, 2008,13(3):531-549.
8 yan R. M., Deci E. L. Intrinsic and extrinsic motivations:Classic definitions and new directions[J]. Contemporary Educational Psychology,2000,25(1):54-67.
9 Ruggiero T.E. Uses and gratification theory in the21 st century[J]. Mass Communication&Society,2000,3(1):3-37.
10 Park N., Kee K.F., Valenzuela S.Being immersed in social networking environment:Facebook groups, uses and gratifications, and social outcomes[J]. CyberPsychology&Behavior, 2009,12(6):729-733.
11 Leung L.Generational differences in content generation in social media:The roles of the gratifications sought and of narcissism[J]. Computers in Human Behavior,2013, 29(3)997-1006.
12 赵英,范娇颖.大学生持续使用社交媒体的影响因素对比研究——以微信、微博和人人网为例[J].情报杂志,2016,35(1):188-195.
13 黄炜,余辉,李岳峰.基于微信用户行为的分享预测模型研究[J].情报理论与实践,2016,39(11):89-94.
14 杨海娟.微信环境下用户适应性信息分享行为影响因素研究——基于规范性压力和社交价值的“推—拉”视角[J].情报科学,2017,35(8):134-140.
15 Barabási A. The origin of bursts and heavy tails in human dynamics[J]. Nature,2005,435(7039):207-211.
16 Ghoshal G, Holme P. Attractiveness and activity in Internet communities[J]. Physica A, 2006,(364):603-609.
17 Yan Q., Wu L., Zheng L. Social network based microblog user behavior analysis[J]. Physica A, 2013, 392(7):1712-1723.
18 Wang C., Guan X., Qin T., et al. Modeling the heterogeneity of human dynamics based on the measurements of influential users in Sina Microblog[J]. Physica A:Statistical Mechanics and its Applications,2015,(428):239-249.
19 辛文娟,赖涵.群体极化视域下网络舆情的演化机制研究——以微博网民讨论“浙江温岭杀医案”为例[J].情报杂志,2015,(2):47-52.
20 Ou C.G., Jin X.L.,Wang Y.Z., Cheng X.Q. Modelling heterogeneous information spreading abilities of social network ties[J].Simulation Modelling Practice and Theory,2017,(75):67-76.
21 Ball B., Newman M. E. Friendship networks and social status[J].Network Science, 2013, 1(1):16-30.
22 Livan G., Caccioli F., Aste T.Excess reciprocity distorts reputation in online social networks[J].Scientific Report, 2017,(7):3551.
23 Pfeil U., Arjan R.,&Zaphiris P. Age differences in online social networking—A study of user profiles and the social capital divide among teenagers and older users in MySpace[J]. Computers in Human Behavior, 2009,(25):643-654.
24 Hargittai E. Whose space? Differences Among Users and Non-Users of Social Network Sites[J]. Journal of Computer-Mediated Communication, 2008,(13):276-297.
25 Wijesundara T. R..Motivations and usage patterns of social networking sites:Exploring cultural differences between United States&Sri Lanka[J]. Canadian Social Science,2015,(10):176-185.
26 Wang J. L., Jackson L. A., Zhang D. J., et al. The relationships among the Big Five Personality factors, self-esteem,narcissism, and sensation-seeking to Chinese University students’uses of social networking sites(SNSs)[J]. Computers in Human Behavior, 2012, 28(6):2313-2319.
27 Hollenbaugh E. E., and Ferris A. L. Facebook self-disclosure:Examining the role of traits, social cohesion, and motives[J]. Computers in Human Behavior, 2014, 30(1):50-58.
28 顾东晓,孙建军,张悦,盛东方,杨苏.基于计划行为理论的用户链接分享研究[J].运筹与管理,2016,25(2):173-179.
29 皇甫军.科研社交网络平台功能因素和用户行为的相关性分析[J].情报科学,2017,35(8):62-67.
30 Goh K.I., Barabási A. L. Burstiness and memory in complex systems[J]. Europhys Lett, 2008, 81(4):48002.