Modelling the factors that determine online news-sharing behaviour of social media users: The role of perceived message and online environmental characteristics

Author:

Na Risu1,Wang Yaqin2,Na Buqi3,Ning Yucheng4,Destiny Apuke Oberiri5ORCID

Affiliation:

1. School of Chinese Language and Literature, Northeast Normal University, China; International Academy of Arts, Jilin International Studies University, China

2. School of Marxism, Changchun University of Science and Technology, China; School of Public Administration, Jilin University, China

3. Material Purchase and Supply Center, Affiliated Hospital of Inner Mongolia Minzu University, China; Graduate School of Language and Culture, Graduate University of Mongolia, China

4. School of Journalism and Communication, Minnan Normal University, China; Cross-Strait Communication Research Center, Minnan Normal University, China

5. Department of Mass Communication, Taraba State University, Jalingo, Nigeria

Abstract

This study modelled the online environment characteristics and message characteristics that predict news sharing among social media users. This study’s data were obtained from a cross-sectional national survey conducted in Nigeria. Qualtrics was used to recruit data from 1320 participants in Nigeria. The participants were recruited via a stratified quota sampling which reflected the country’s census statistics for gender and age. We found the message characteristics to predict news-sharing behaviour among social media users in Nigeria. By implication, the characteristics of a message encountered online influence the news-sharing behaviour of social media users. We also found that the online environment characteristics predict news-sharing behaviour, which implies that the external factor, that is, the relationship a user has with his network members, predicts sharing behaviour. Some theoretical and practical implications were provided to conclude the study.

Publisher

SAGE Publications

Subject

Library and Information Sciences,Information Systems

Reference76 articles.

1. Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention

2. Gever CV. Why does misinformation about COVID-19 strive on social media platforms? Suggesting an intervention strategy for Nigerian government. Ianna J Interdiscip Stud 2021; 2(1), https://iannajournalofinterdisciplinarystudies.com/index.php/1/article/view/32

3. Why Do People Share News in Social Media?

4. Why Users Share the News: A Theory of Reasoned Action-Based Study on the Antecedents of News-Sharing Behavior

5. News and newsworthiness: A commentary

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3