Influence of Video Comments Characteristics on Viewers' Commenting Behaviors——Taking Bilibili as an Example

  • Pu Zheyuan ,
  • Li Shengli
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  • Department of Information Management, Peking University, Beijing 100871

Received date: 2022-07-29

  Revised date: 2022-09-05

  Online published: 2022-11-17

Abstract

[Purpose/Significance] The commenting and publishing behaviors of viewers in online video communities reflect the social interaction between viewers and video uploaders as well as among viewers. Exploring the influencing factors of users' commenting behaviors in online video communities is of great significance in strengthening the relationship among users in video communities and motivate their participation. [Method/Process] Based on the N-effect, signaling theory, and social presence theory, this paper proposed hypotheses regarding how characteristics of the existing comments may influence viewers' comment posting behaviors. The daily data of 2075 videos published on BiliBili.com at the same day were tracked for one week. The two-way fixed effect model was used to test our hypotheses. [Result/Conclusion] The number of peer comments has a negative impact on video viewers' comment posting behaviors, and the comment feedback from video uploaders has a positive impact on viewers' comment posting behaviors. The users' interactivity of the existing comments can weaken the impacts of both the number of peer comments and video uploaders' comment feedback on viewers' comment posting behaviors.

Cite this article

Pu Zheyuan , Li Shengli . Influence of Video Comments Characteristics on Viewers' Commenting Behaviors——Taking Bilibili as an Example[J]. Library and Information Service, 2022 , 66(20) : 130 -140 . DOI: 10.13266/j.issn.0252-3116.2022.20.014

References

[1] ROTMAN D, PREECE J. The 'Wetube’ in YouTube - creating an online community through video sharing[J].International journal of Web based communities,2010,6(3):317-333.
[2] 中国互联网络信息中心.中国互联网络发展状况统计报告[EB/OL].(2021-09-15)[2022-07-13].http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202109/P020210915523670981527.pdf.
[3] SHOHAM M D, ARORA A B, AL-BUSAIDI A, et al. Writing on the wall: an online "community" of YouTube patrons as communication network or cyber-graffiti?[C]//Proceedings of the 46th Hawaii international conference on system sciences. Piscataway:IEEE,2013.
[4] IRIBERRI A, LEROY G. A life-cycle perspective on online community success[J].ACM computing surveys,2009,41(2):1-29.
[5] KREIJNS K, KIRSCHNER P A, JOCHEMS W, et al. Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research[J].Computers in human behavior,2003,19(3):335-353.
[6] CHEN C-C, LIN Y-C. What drives live-stream usage intention? the perspectives of flow, entertainment, social interaction, and endorsement[J]. Telematics and informatics,2018,35(1):293-303.
[7] 甘春梅.社交媒体使用动机与功能使用的关系研究:以微信为例[J].图书情报工作,2017,61(11):106-115.
[8] BARNES R, MAHAR D, WONG I, et al. A neurotic extrovert who is open to new experiences: understanding how personality traits may impact the commenting behaviors of online news readers[J].Journal of broadcasting & electronic media,2017,61(3):557-573.
[9] KANGASPUNTA V. Internet users’ reasons and motives for online news commenting[J].International journal of communication,2021,15(23):4480-4502.
[10] KALOGEROPOULOS A, NEGREDO S, PICONE I, et al. Who shares and comments on news? a cross-national comparative analysis of online and social media participation[J].Social media + society,2017,3(4):1-12.
[11] ZIEGELE M, WEBER M, QUIRING O, et al. The dynamics of online news discussions: effects of news articles and reader comments on users’ involvement, willingness to participate, and the civility of their contributions[J].Information, communication & society,2017,21(10):1419-1435.
[12] KSIAZEK T B. Commenting on the news[J].Journalism studies,2016,19(5):650-673.
[13] SCHÄFER S, MÜLLER P, ZIEGELE M, et al. The double-edged sword of online deliberation: how evidence-based user comments both decrease and increase discussion participation intentions on social media[OL].New media & society,2022:1-26.
[14] WANG K C, LAI C M, WANG T, et al. Bandwagon effect in facebook discussion groups[C]//Proceedings of the ASE bigdata & social informatics. New York: Association for Computing Machinery,2015:1-6.
[15] 尹敬刚,李晶,魏登柏.移动互联网环境下发表评论意愿的影响因素研究——一个整合模型的视角[J].图书情报工作,2012,56(2):135-141.
[16] CHEUNG C M K, LEE M K O. What drives consumers to spread electronic word of mouth in online consumer-opinion platforms[J].Decision support systems,2012,53(1):218-225.
[17] KHAN M L. Social media engagement: what motivates user participation and consumption on YouTube?[J].Computers in human behavior,2017,66:236-247.
[18] 张辉,徐晓林.博客评论行为动机因素实证研究[J].情报杂志,2013,32(11):107-109,201.
[19] 冯小东,张会平.兴趣驱动的政务微博公众评论行为影响模型及实证研究[J].电子政务,2018(11):23-33.
[20] SOFFER O, GORDONI G. To post or not to post? anonymous user comments in the Israeli journalistic sphere[J].Journalism studies,2018,19(10):1390-1408.
[21] ZIEGELE M, JOST P B. Not funny? the effects of factual versus sarcastic journalistic responses to uncivil user comments[J].Communication research,2020,47(6):891-920.
[22] 孙悦,黄微.社交媒体平台用户参与的行为谱与行为层级模型构建[J].图书情报工作,2022,66(9):40-52.
[23] 殷猛,李琪.基于羊群效应和动机理论的微博话题参与意愿研究[J].情报科学,2017,35(4):150-155.
[24] 毕德强,黄世晴,董颖,等.科研用户学术社交网络认知与使用动机比较研究[J].图书情报工作,2019,63(6):97-102.
[25] 冯钰茹,邓小昭.弹幕视频网站用户弹幕评论行为的影响因素研究——以Bilibili弹幕视频网站为例[J].图书情报工作,2021,65(17):110-116.
[26] TURNER J H. A theory of social interaction[M].Stanford: Stanford University Press,1988.
[27] SPRINGER N, ENGELMANN I, PFAFFINGER C. User comments: motives and inhibitors to write and read[J].Information, communication & society,2015,18(7):798-815.
[28] FEROZ KHAN G, VONG S. Virality over YouTube: an empirical analysis[J]. Internet research,2014,24(5):629-647.
[29] GARCIA S M, TOR A. The n-effect[J].Psychological science,2009,20(7):871-877.
[30] LU S, YAO D, CHEN X, et al. Do larger audiences generate greater revenues under pay what you want? evidence from a live streaming platform[J].Marketing science,2021,40(5):964-984.
[31] MEYER H K, CAREY M C. In moderation: examining how journalists’ attitudes toward online comments affect the creation of community[J].Journalism practice,2014,8(2):213-228.
[32] WAN Y. The Matthew Effect in social commerce[J].Electronic markets,2015,25(4):313-324.
[33] LEW Z, STOHL C. What makes people willing to comment on social media posts? the roles of interactivity and perceived contingency in online corporate social responsibility communication[J].Communication monographs,2022:1-24.
[34] SPENCE M. Job market signaling[J].The quarterly journal of economics,1973,87(3):355-374.
[35] 唐坤孟,李胜利,张倩.患者在线医疗团队服务选择行为影响因素研究——以好大夫在线为例[J].图书情报工作,2021,65(11):33-45.
[36] CHEN Y, LU Y, WANG B, et al. How do product recommendations affect impulse buying? an empirical study on WeChat social commerce[J]. Information & management,2019,56(2):236-248.
[37] 毛春蕾,袁勤俭.社会临场感理论及其在信息系统领域的应用与展望[J].情报杂志,2018,37(8):186-194.
[38] ALGHARABAT R, RANA N P, DWIVEDI Y K, et al. The effect of telepresence, social presence and involvement on consumer brand engagement: an empirical study of non-profit organizations[J].Journal of retailing and consumer services,2018,40:139-149.
[39] CHEIKH-AMMAR M, BARKI H. The influence of social presence, social exchange and feedback features on SNS continuous use[J].Journal of organizational and end user computing,2016,28(2):33-52.
[40] BUCY E P. Interactivity in society: locating an elusive concept[J].The information society,2004,20(5):373-383.
[41] ZIEGELE M, BREINER T, QUIRING O. What creates interactivity in online news discussions? an exploratory analysis of discussion factors in user comments on news items[J].Journal of communication,2014,64(6):1111-1138.
[42] 甘春梅,王伟军.学术博客持续使用意愿:交互性、沉浸感与满意感的影响[J].情报科学,2015,33(3):70-74,94.
[43] 庄倩,骆慧颖,戴岽丞,等.用户交互对社会标注行为的差异影响研究——以豆瓣网为例[J].图书情报工作,2020,64(20):117-128.
[44] 邓胜利,蒋雨婷.用户交互特征对知识付费行为预测的贡献度研究[J].图书情报工作,2020,64(8):93-102.
[45] bilibili. 关于我们[EB/OL].[2022-05-10].https://www.bilibili.com/blackboard/aboutUs.html.
[46] WINSHIP C, MORGAN S L. The estimation of causal effects from observational data[J].Annual review of sociology,1999,25(1):659-706.
[47] 孙晶,李涵硕.金融集聚与产业结构升级——来自2003-2007年省际经济数据的实证分析[J].经济学家,2012(3):80-86.
[48] ABADIE A, ATHEY S, IMBENS G W, et al. When should you adjust standard errors for clustering?[R/OL].[2022-07-15].https://www.nber.org/papers/w24003.
[49] 连玉君,廖俊平.如何检验分组回归后的组间系数差异?[J].郑州航空工业管理学院学报,2017,35(6):97-109.
[50] LANZ A, GOLDENBERG J, SHAPIRA D, et al. Climb or jump: status-based seeding in user-generated content networks[J].Journal of marketing research,2019,56(3):361-378.
[51] PHILLIPS K W, ROTHBARD N P, DUMAS T L, et al. To disclose or not to disclose? status distance and self-disclosure in diverse environments[J].Academy of management review,2009,34(4):710-732.作者贡献说明: 普哲缘:设计研究方案,采集、清洗和分析数据,撰写论文; 李胜利:提出研究思路,完善研究方案,修订论文。
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