信息过载视角下用户创建资源列表扩散效果的影响因素研究——以网易云音乐为例
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摘要
[目的/意义]选取歌单这一典型用户自发组织平台资源创建资源列表模式,探索"什么样的用户创建资源列表更受欢迎"的问题,揭示用户创建资源列表内容丰富度可能引发的信息冗余现象。[方法/过程]基于信息接受理论与信息过载视角,构建用户创建资源列表扩散的信息接受模型,借助爬虫软件获取网易云音乐歌单相关数据,研究资源列表创建者特征、资源列表质量特征对资源列表扩散效果的影响。[结果/结论]网易云音乐中用户社交网络具有无标度特征;创建者活跃度和贡献度对网络中心性产生正向影响;创建者网络中心性、网络活跃度、网络贡献度、资源列表介绍长度对资源列表有用性和资源列表扩散效果均有显著正向影响;资源列表内容丰富度与资源列表有用性、资源列表扩散效果均存在倒U型关系;在资源列表质量特征对资源列表扩散效果的影响中,资源列表有用性起到了中介作用。
[Purpose/Significance]This study selected song list,a typical user spontaneous organization platform resource to create a resource list,exploring the question"What kind of user generated resource list(UGRL)is more popular",and revealing the information redundancy that may arise from the richness of user generated resource list.[Method/Process]Based on the theory of information acceptance theory and the perspective of information overload,this study constructed the information acceptance model of user generated resource list diffusion,and used the crawler software to obtain the data of Netease cloud music song list and song list creator,and studied the influences of UGRL creator characteristics and UGRL quality characteristics on the UGRL diffusion effect.[Result/Conclusion]The user social network in Netease Cloud Music has a scale-free feature;the creator's activity and contribution have a positive impact on the network centrality;The creator's network centrality,network activity,network contribution,UGRL introduction length have a significant positive impact on UGRL usefulness and UGRL diffusion effect;There was an inverted U-shaped relationship between UGRL content richness and UGRL usefulness,and also between UGRL content richness and UGRL diffusion effect;In the influence of the UGRL quality characteristics on the UGRL diffusion affect,the UGRL usefulness played a mediation role.
[Purpose/Significance]This study selected song list,a typical user spontaneous organization platform resource to create a resource list,exploring the question"What kind of user generated resource list(UGRL)is more popular",and revealing the information redundancy that may arise from the richness of user generated resource list.[Method/Process]Based on the theory of information acceptance theory and the perspective of information overload,this study constructed the information acceptance model of user generated resource list diffusion,and used the crawler software to obtain the data of Netease cloud music song list and song list creator,and studied the influences of UGRL creator characteristics and UGRL quality characteristics on the UGRL diffusion effect.[Result/Conclusion]The user social network in Netease Cloud Music has a scale-free feature;the creator's activity and contribution have a positive impact on the network centrality;The creator's network centrality,network activity,network contribution,UGRL introduction length have a significant positive impact on UGRL usefulness and UGRL diffusion effect;There was an inverted U-shaped relationship between UGRL content richness and UGRL usefulness,and also between UGRL content richness and UGRL diffusion effect;In the influence of the UGRL quality characteristics on the UGRL diffusion affect,the UGRL usefulness played a mediation role.
引文
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[9]李晶,漆贤军,陈明红.信息质量感知对信息获取与信息采纳的影响研究[J].情报科学,2015,(3):123-129.
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[12]王娜,任婷.移动社交网站中的信息过载与个性化推荐机制研究[J].情报杂志,2015,34(8):190-194.
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[14]李旭,刘鲁川.信息过载背景下社会化阅读APP用户的忽略与退出行为——心理契约违背视角[J].图书馆,2018,(2):75-84.
[15]Mudambi S M,Schuff D.What Makes a Helpful Online Review?A Study of Customer Reviews on amazon.com[J].MIS Q,2010,34(1):185-200.
[16]Chevalier J A,Mayzlin D.The Effect of Word of Mouth on Sales:Online Book Reviews[J].Journal of Marketing Research,2006,43(3):345-354.
[17]Johnson E J,Payne J W.Effort and Accuracy in Choice[J].Management Science,1985,31(4):395-414.
[18]王娜,张丽娟.UGC社区中的信息过载防控机制研究[J].创新科技,2016,(3):91-93.
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[21]Susarla A,Oh J H,Tan Y.Social Networks and the Diffusion of User-Generated Content:Evidence from YouTube[J].Information Systems Research,2012,23(1):23-41.
[22]何旵阳,孙鲁敬,杨家海.基于Feeds的社交网络活跃度分析[J].计算机科学,2015,(11):149-153.
[23]万岩,范静,高锦萍,等.网络社群的凝聚力与活跃度提升研究:品牌与信任的角度[J].系统管理学报,2017,(4):611-623.
[24]孙怡,鲁耀斌,魏国基.社交氛围对朋友群组成员的购买意愿和行为的影响[J].管理学报,2016,(9):1392-1399.
[25]肖邦明,黄敏学,廖俊云.交易型社区的网络闭包机制研究[J].管理科学,2015,(5):129-144.
[26]周军杰.社会化商务背景下的用户粘性:用户互动的间接影响及调节作用[J].管理评论,2015,(7):127-136.
[27]冉晓斌,刘跃文,姜锦虎.社交网络活跃行为的大数据分析:网络外部性的视角[J].管理科学,2017,(5):77-86.
[28]Chen R.Member Use of Social Networking Sites—An Empirical Examination[J].Decision Support Systems,2013,54(3):1219-1227.
[29]Rau P P,Gao Q,Ding Y.Relationship Between the Level of Intimacy and Lurking in Online Social Network Services[J].Computers in Human Behavior,2008,24(6):2757-2770.
[30]Trusov M,Bodapati A V,Bucklin R E.Determining Influential Users in Internet Social Networks[J].Journal of Marketing Research,2010,47(4):643-658.
[31]Chen A,Lu Y,Chau P Y K,et al.Classifying,Measuring,and Predicting Users’ Overall Active Behavior on Social Networking Sites[J].Journal of Management Information Systems,2014,31(3):213-253.
[2]崔金红,汪凌韵.在线反馈系统中消费者网络口碑传播动机的实证研究[J].现代图书情报技术,2012,(10):55-60.
[3]Yu-Wei C,Ping-Yu H,Wen-Lung S,et al.The Effect of Customer Power on Enterprise Internal Knowledge Sharing:An Empirical Study[J].Aslib Journal of Information Management,2015,67(5):505-525.
[4]Moe W W,Schweidel D A.Online Product Opinions:Incidence,Evaluation,and Evolution[J].Marketing Science,2012,31(3):372-386.
[5]Susarla A,Oh J,Tan Y.Social Networks and the Diffusion of User-Generated Content:Evidence from YouTube[J].Information Systems Research,2012,23(1):23-41.
[6]Shriver S K,Nair H S,Hofstetter R.Social Ties and User-Generated Content:Evidence from an Online Social Network[J].Management Science,2013,59(6):1425-1443.
[7]夏立新,王凯利,程秀峰.基于PPM模型的移动音乐平台用户转移行为研究——以网易云音乐为例[J].现代情报,2018,(8):3-11.
[8]Sussman S W,Siegal W S.Informational Influence in Organizations:An Integrated Approach to Knowledge Adoption[J].Information Systems Research,2003,14(1):47-65.
[9]李晶,漆贤军,陈明红.信息质量感知对信息获取与信息采纳的影响研究[J].情报科学,2015,(3):123-129.
[10]李进华,张婷婷.社会化问答知识分享用户感知有用性影响因素研究——以知乎为例[J].现代情报,2018,(4):20-28.
[11]徐瑞朝,曾一昕.国内信息过载研究述评与思考[J].图书馆学研究,2017,(18):21-25.
[12]王娜,任婷.移动社交网站中的信息过载与个性化推荐机制研究[J].情报杂志,2015,34(8):190-194.
[13]刘雪琪,廖秉宜.我国大陆地区新浪微博用户信息过载感知程度影响因素的实证研究[J].信息资源管理学报,2017,7(3):66-72.
[14]李旭,刘鲁川.信息过载背景下社会化阅读APP用户的忽略与退出行为——心理契约违背视角[J].图书馆,2018,(2):75-84.
[15]Mudambi S M,Schuff D.What Makes a Helpful Online Review?A Study of Customer Reviews on amazon.com[J].MIS Q,2010,34(1):185-200.
[16]Chevalier J A,Mayzlin D.The Effect of Word of Mouth on Sales:Online Book Reviews[J].Journal of Marketing Research,2006,43(3):345-354.
[17]Johnson E J,Payne J W.Effort and Accuracy in Choice[J].Management Science,1985,31(4):395-414.
[18]王娜,张丽娟.UGC社区中的信息过载防控机制研究[J].创新科技,2016,(3):91-93.
[19]Schick A G,Gordon L A,Haka S.Information Overload:A Temporal Approach[J].Accounting,Organizations and Society,1990,15(3):199-220.
[20]Forman C,Ghose A,Wiesenfeld B.Examining the Relationship Between Reviews and Sales:The Role of Reviewer Identity Disclosure in Electronic Markets[J].Information Systems Research,2008,19(3):291-313.
[21]Susarla A,Oh J H,Tan Y.Social Networks and the Diffusion of User-Generated Content:Evidence from YouTube[J].Information Systems Research,2012,23(1):23-41.
[22]何旵阳,孙鲁敬,杨家海.基于Feeds的社交网络活跃度分析[J].计算机科学,2015,(11):149-153.
[23]万岩,范静,高锦萍,等.网络社群的凝聚力与活跃度提升研究:品牌与信任的角度[J].系统管理学报,2017,(4):611-623.
[24]孙怡,鲁耀斌,魏国基.社交氛围对朋友群组成员的购买意愿和行为的影响[J].管理学报,2016,(9):1392-1399.
[25]肖邦明,黄敏学,廖俊云.交易型社区的网络闭包机制研究[J].管理科学,2015,(5):129-144.
[26]周军杰.社会化商务背景下的用户粘性:用户互动的间接影响及调节作用[J].管理评论,2015,(7):127-136.
[27]冉晓斌,刘跃文,姜锦虎.社交网络活跃行为的大数据分析:网络外部性的视角[J].管理科学,2017,(5):77-86.
[28]Chen R.Member Use of Social Networking Sites—An Empirical Examination[J].Decision Support Systems,2013,54(3):1219-1227.
[29]Rau P P,Gao Q,Ding Y.Relationship Between the Level of Intimacy and Lurking in Online Social Network Services[J].Computers in Human Behavior,2008,24(6):2757-2770.
[30]Trusov M,Bodapati A V,Bucklin R E.Determining Influential Users in Internet Social Networks[J].Journal of Marketing Research,2010,47(4):643-658.
[31]Chen A,Lu Y,Chau P Y K,et al.Classifying,Measuring,and Predicting Users’ Overall Active Behavior on Social Networking Sites[J].Journal of Management Information Systems,2014,31(3):213-253.