| 社交媒体用户消极使用行为：多源数据融合视角 |
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| 引用本文： | 范春竹,邓小昭,韩毅.社交媒体用户消极使用行为：多源数据融合视角[J].图书情报工作,2022,66(15):76-85. |
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| 作者姓名： | 范春竹 邓小昭 韩毅 |
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| 作者单位： | 1. 西南大学计算机与信息科学学院 重庆 400715;2. 西南大学商贸学院 重庆 402460 |
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| 摘 要： | 目的/意义]通过融合不同来源数据的方式探索社交媒体用户消极使用行为影响因素,为用户健康合理地可持续使用社交媒体提供理论支撑,并为平台改进服务提供参考信息。方法/过程]对访谈数据进行三级编码,结合爬虫获取的包含部分受访者数据的用户行为轨迹数据分析社交媒体用户消极使用原因,构建社交媒体用户消极使用行为影响因素模型。结果/结论]通过多源数据融合能够解决单一来源数据有效性不足问题。研究发现外部环境因素(任务情境、信息过载、社交过载、不良言论)和平台因素(系统功能、品牌形象、付费服务)通过内部个人因素(信息需求、认知差异、负面情绪、使用成本、使用习惯、隐私关注)影响用户使用社交媒体,产生潜水、屏蔽、间歇使用、转移、退出和抵制等不同程度的消极使用行为,一定程度上反映了用户作为弱势对象在技术环境下的自我保护。
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| 关 键 词： | 社交媒体用户 消极使用行为 影响因素模型 多源数据融合 |
| 收稿时间： | 2022-01-17 |
| 修稿时间： | 2022-06-02 |
Researches on Passive Behavior for Social Media Users：From the Perspective of the Fusion of Multi-Source Data |
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| 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. |
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| Authors: | Fan Chunzhu Deng Xiaozhao Han Yi |
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| Institution: | 1. Computer and Information Science College, Southwest University, Chongqing 400715;2. Business College, Southwest University, Chongqing 402460 |
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| Abstract: | 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. |
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| Keywords: | social media users passive use behavior influence factor model multi-source data fusion |
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