心理学
社会化媒体
信息过载
情感(语言学)
独创性
透视图(图形)
社会心理学
认知
万维网
创造力
计算机科学
沟通
人工智能
神经科学
作者
Dai Bao,Ahsan Ali,Hongwei Wang
出处
期刊:Internet Research
[Emerald (MCB UP)]
日期:2020-07-14
卷期号:30 (5): 1455-1478
被引量:101
标识
DOI:10.1108/intr-06-2019-0225
摘要
Purpose Grounded on the cognition–affect–conation (C–A–C) framework, this study aims to explore how perceived information overload affects the information avoidance intention of social media users through fatigue, frustration and dissatisfaction. Design/methodology/approach/methodology/approach A quantitative research design is adopted. The data collected from 254 respondents in China are analyzed via structural equation modeling (SEM). Findings Perceived information overload directly affects fatigue, frustration and dissatisfaction among social media users, thereby affecting their information avoidance intention. In addition, frustration significantly affects social media fatigue and dissatisfaction. Consequently, social media fatigue influences dissatisfaction among users. Originality/value The literature review indicates that social media overload and fatigue yield negative behavioral outcomes, including discontinuance. However, rather than completely abstaining or escaping, social media users adopt moderate strategies, including information avoidance, to cope with overload and fatigue owing to their high dependence on social media. Unfortunately, merely few studies are available on the information avoidance behavior of social media users. Focusing on this line of research, the current study develops a model to investigate the antecedents of information avoidance in social media.
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