Is Snapchat Discover really a news platform? News snacking from social media and users’ knowledge of current affairs

IF 0.4 Q4 COMMUNICATION Journal of Applied Journalism & Media Studies Pub Date : 1900-01-01 DOI:10.1386/ajms_00047_1
Jayeon Lee
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引用次数: 1

Abstract

The role of the media in informing the public has long been a central topic in journalism studies. Given that social media platforms have become today’s major source of news, it is important to understand the impact of social media use on citizens’ knowledge of current affairs. While people get news from multiple platforms throughout the day, most research treats social media as a single entity or examines only one or two major platforms ignoring newer social media platforms. Drawing on news snacking framework, this study investigates how using some of today’s most popular social media platforms predicts users’ current affairs knowledge, with particular attention to Snapchat and its news section Discover. A survey conducted in the United States (N=417) demonstrated that each of the platforms is distinct: Twitter is a strongly positive predictor of knowledge, Facebook a marginally significant negative predictor, Reddit a significantly negative predictor and Instagram not a significant predictor. Overall Snapchat use has no significant association with users’ knowledge of current affairs, whereas Discover use has a negative relationship. Further analysis revealed that mere exposure to Snapchat is positively related to soft-news knowledge and attention to Discover is negatively related to hard-news knowledge.
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Snapchat Discover真的是一个新闻平台吗?从社交媒体和用户的时事知识中获取新闻
长期以来,媒体在向公众传播信息方面的作用一直是新闻学研究的中心话题。鉴于社交媒体平台已成为当今新闻的主要来源,了解社交媒体使用对公民时事知识的影响非常重要。虽然人们每天从多个平台获取新闻,但大多数研究都将社交媒体视为一个单一实体,或者只调查一两个主要平台,而忽略了较新的社交媒体平台。利用新闻零食框架,本研究调查了使用当今最流行的一些社交媒体平台如何预测用户的时事知识,特别关注Snapchat及其新闻部分Discover。在美国进行的一项调查(N=417)表明,每个平台都是不同的:Twitter是知识的强烈积极预测因素,Facebook是略微显著的负面预测因素,Reddit是显著的负面预测因素,Instagram不是显著的预测因素。总的来说,Snapchat的使用与用户对时事的了解没有显著的关联,而Discover的使用则与之呈负相关。进一步分析发现,仅仅接触Snapchat与软新闻知识正相关,关注Discover与硬新闻知识负相关。
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来源期刊
CiteScore
1.70
自引率
0.00%
发文量
20
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