[Purpose/Significance] This paper explores the influencing factors of passive use behaviors for social media users by fusing data from different sources, so as to provide theoretical support for the healthy, reasonable and sustainable use of social media for users, and to provide references for improving services of the platform. [Method/Process] The interview data were coded through three steps. And in combination with users' behavior trace data - including some interviewee data - obtained by Web crawlers, the reasons for the negative use of social media users were analyzed, and the influencing factors model of passive use behaviors of social media users was constructed. [Result/Conclusion] The problem of insufficient validity of single-source data can be solved through multi-source data fusion. It is found that external environmental factors (task context, information overload, social overload, bad speech) and platform factors (system functions, brand image, paid services) affect social media users' behaviors through internal personal factors (information needs, cognitive differences, negative emotions, usage costs, usage habits, privacy concerns), resulting in different degrees of passive behaviors, such as diving, shielding, intermittent using, switching, withdrawing and resisting. To a certain extent, it reflects the self-protection of users as vulnerable objects in the technical environment.
Fan Chunzhu
,
Deng Xiaozhao
,
Han Yi
. Researches on Passive Behavior for Social Media Users:From the Perspective of the Fusion of Multi-Source Data[J]. Library and Information Service, 2022
, 66(15)
: 76
-85
.
DOI: 10.13266/j.issn.0252-3116.2022.15.008
[1] 凯度集团.2018年中国社交媒体影响报告[EB/OL].[2021-03-28]. http://www.199it.com/archives/820382.html.
[2] 刘鲁川,李旭,张冰倩.社交媒体用户的负面情绪与消极使用行为研究评述[J].情报杂志,2018,37(1):105-113,121.
[3] BURKE M, MARLOW C, LENTO T. Social network activity and social well-being [C] // Proceedings of the SIGCHI conference on human factors in computing systems. New York: ACM, 2010, 93(2): 1909-1912.
[4] 李红云.新浪微博不持续使用影响因素的实证研究[D].大连:大连理工大学,2017.
[5] 刘鲁川,李旭,张冰倩.基于扎根理论的社交媒体用户倦怠与消极使用研究[J].情报理论与实践,2017,40(12):100-106,51.
[6] 张敏,孟蝶,张艳.强关系社交媒体用户消极使用行为形成机理的概念模型——基于使能和抑能的双重视角的扎根分析[J].现代情报,2019,39(4):42-50.
[7] 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.
[8] 程慧平,苏超,王建亚.社交媒体用户不持续使用行为模型构建及实证研究[J].情报学报,2020,39(9):963-978.
[9] ZHU X H, BAO Z S. Why people use social networking sites passively: an empirical study integrating impression management concern, privacy concern, and SNS fatigue [J]. Aslib journal of information management, 2018, 70(2): 158-175.
[10] 刘国亮,张汇川,刘子嘉.移动社交媒体用户不持续使用意愿研究——整合错失焦虑与社交媒体倦怠双重视角[J].情报科学,2020,38(12):128-133.
[11] 李旭.信息过载背景下社交媒体用户倦怠及消极使用行为研究[D].济南:山东财经大学,2018.
[12] 唐天娇.社会化阅读平台用户不持续使用行为影响因素研究[D].武汉:华中师范大学,2019.
[13] RAVINDRAN T, KUAN A, LIAN D. Antecedents and effects of social network fatigue [J]. Journal of the Association for Information Science and Technology, 2014, 65(11): 2306-2620.
[14] 李君君,王金歌,曹园园.间歇性中辍行为特征的探索性研究——以微博数据为例[J].现代情报,2021,41(1):60-66.
[15] WILSON T D. Human information behavior [J]. Informing science: the international journal of an emerging transdiscipline, 2000, 3(2): 49-56.
[16] YORK C, TURCOTTE J. Vacationing from Facebook: adoption, temporary discontinuance, and readoption of an innovation [J]. Communication research reports, 2015, 32(1): 54-62.
[17] 明均仁,操慧子.移动图书馆用户的不持续使用行为影响因素研究——以超星移动图书馆为例[J].情报理论与实践,2021,44(3):157-163.
[18] 贾若男,王晰巍.基于扎根理论的社交媒体用户转移行为特征研究[J].图书馆学研究,2018(17):26-33.
[19] 邹丹,韩毅.孕妇信息规避行为的影响因素研究[J].图书情报工作,2017,61(17):91-98.
[20] 王文韬,张帅,李晶,等.个人信息回避行为的驱动因素研究[J].现代情报,2018,38(4):29-34.
[21] PAGANI M, MALACARNE G. Experiential engagement and active vs. passive behavior in mobile location-based social networks: the moderating role of privacy [J]. Journal of interactive marketing, 2017, 37(1): 133-148.
[22] CAO XIONGFEI, KHAN A, ALI A, et al. Consequences of cyberbullying and social overload while using SNSs: a study of users' discontinuous usage behavior in SNSs [J]. Information systems frontiers, 2019, 22(2): 1343-1356.
[23] RYMARCZUK R. Same old story: on non-use and resistance to the telephone and social media [J]. Technology in society, 2016, 45(5): 40-47.
[24] 王晰巍,李嘉兴,王铎,等.移动社交媒体老年用户抵制行为影响因素研究:基于人-系统交互理论视角的分析[J].情报资料工作,2019,40(1):81-88.
[25] 张艳丰,彭丽徽,洪闯,等.因果要素关联视域下社交媒体倦怠用户画像模型构建[J].图书情报工作,2019,63(14):94-100.
[26] 郑德俊,李杨,沈军威,等.移动阅读服务平台的用户流失因素分析——以"微信读书"平台为例[J].情报理论与实践,2019,42(8):78-82.
[27] 王文韬,张帅,李晶,等.大学生健康信息回避行为的驱动因素探析及理论模型建构[J].图书情报工作,2018,62(3):5-11.
[28] 蔺丰奇,刘益.信息过载问题研究述评[J].情报理论与实践,2007,30(5):710-714.
[29] 刘咏梅,张帅,谢阳群.社交网络环境下大学生信息回避行为影响因素探究[J].现代情报,2019,39(10):58-65.
[30] WU Y L, TAO Y H, LI C P, et al. User-switching behavior in social network sites: a model perspective with drill-down analyses [J]. Computers in human behavior, 2014, 43(2): 241-272.