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浏览抑或阅读?社交媒体用户对偶遇新闻的处理策略研究
Browsing or Reading? A Study of Social Media Users' Strategies for Processing Incidental News
新闻偶遇是社交媒体用户接触新闻的重要方式，对偶遇新闻的不同处理策略影响用户的知识获取、新闻参与和社会参与，但现有研究很少关注用户对偶遇新闻的处理策略，这使得新闻偶遇的效果研究缺乏知识累积性。论文基于PINE模型，将偶遇新闻处理策略分为浏览和阅读，并采用组态分析方法，从用户、社交网络、内容三个维度出发选取因素，研究各因素如何通过复杂的组合和互动影响用户对偶遇新闻的处理策略。研究发现了社交媒体用户浏览和阅读偶遇新闻各自的条件组态，认为新闻线索和社交线索共同决定用户对偶遇新闻的处理策略。研究结果揭示了社交媒体用户处理偶遇新闻的原因，并对新闻偶遇的现有理论进行了实证检验和理论整合。
Incidental news exposure is a crucial way for social media users to encounter news. Different strategies for handling incidental news exposure affect users' knowledge acquisition, news engagement, and social participation. However, existing research has rarely focused on users' strategies for dealing with incidental news, leading to a lack of cumulative knowledge in studying the effects of incidental news exposure. This paper, based on the PINE model, categorizes incidental news handling strategies into browsing and reading. Using a configuration analysis approach, it examines key factors across three dimensions—user, social network, and content—to study how these factors interact and combine to influence users' handling strategies for incidental news. The research identifies the specific conditions under which social media users browse or read incidental news and finds that both news cues and social cues jointly determine users’ strategies for handling incidental news. The results reveal the reasons behind social media users’ handling of incidental news and provide empirical validation and theoretical integration of existing theories on incidental news exposure.
Incidental news exposure / social media / news engagement / configuration analysis
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Some people live in social media “news deserts,” while others are embedded in online networks that are rich in news content. These news deserts represent a new form of digital inequality—distinct from problems of access, resources, or civic skills—that could foreclose one of the ways social media are believed to contribute to informing citizens and engaging them in democratic processes: providing opportunities for incidental news exposure. This study investigates incidental exposure on social media platforms, drawing on an online survey administered just before the 2018 US Midterm Elections ( N = 1493). The study finds that even after controlling for key individual-level factors, characteristics of social media discussion networks play a role in explaining variation in incidental exposure. The results are discussed in light of prevailing theory about incidental exposure, public engagement, and digital inequalities.
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Theoretical “necessary but not sufficient” statements are common in the organizational sciences. Traditional data analyses approaches (e.g., correlation or multiple regression) are not appropriate for testing or inducing such statements. This article proposes necessary condition analysis (NCA) as a general and straightforward methodology for identifying necessary conditions in data sets. The article presents the logic and methodology of necessary but not sufficient contributions of organizational determinants (e.g., events, characteristics, resources, efforts) to a desired outcome (e.g., good performance). A necessary determinant must be present for achieving an outcome, but its presence is not sufficient to obtain that outcome. Without the necessary condition, there is guaranteed failure, which cannot be compensated by other determinants of the outcome. This logic and its related methodology are fundamentally different from the traditional sufficiency-based logic and methodology. Practical recommendations and free software are offered to support researchers to apply NCA.
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Incidental exposure to shared news on Facebook is a vital but understudied aspect of how citizens get involved with politics. This experiment investigates the influence of recommender characteristics (tie strength, political knowledge, political similarity) and different media sources (tabloids, legacy, and digital-born outlets) including multiple mediators (e.g., social pressure, outlet credibility) on incidental exposure to political news on Facebook. A 3 × 3 multi-stimulus, between-subject experiment with two additional quasi-factors and 135 different stimuli was conducted using a representative sample ( N = 507). Results showed that strong ties and recommenders with high knowledge increase news exposure, but the impact of knowledge is limited to recommenders with similar political opinions. Similar effects occur for different media types, which also have an independent impact on news exposure. Structural equation modeling reveals that media source effects are mediated through media perceptions, whereas recommender effects work via the desire for social monitoring and perceived issue importance.
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Social network sites such as Facebook and Twitter have become a key part of online users’ news diets. On social network sites, even individuals who are not motivated to seek out news are believed to be exposed to news posts due to the sharing activities of friends or inadvertently witnessing discussions about current events. Research on this incidental news exposure (INE) has largely focused on its potential for positive effects on information gain or political participation, while simultaneously turning a blind eye to the inequalities in news exposure and engagement. This article aims to address this issue by proposing and explicating the existence of a ‘Matthew Effect’ in social media news use. It is argued that INE research needs to consider the unequal chances to both be exposed to news on social network sites and to actually engage (i.e. read and interact) with ‘accidentally’ encountered news content.
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This article outlines the Political Incidental News Exposure Model. The Political Incidental News Exposure Model understands incidental news exposure as a dynamic process and distinguishes two levels of incidental news exposure: the passive scanning of incidentally encountered political information (first level) and the intentional processing of incidentally encountered content appraised as relevant (second level). After encountering political information incidentally, recipients briefly check the content for relevance (i.e., first level). If content is appraised as relevant, recipients switch to more intensive processing (i.e., second level incidental news exposure). Importantly, second-level incidental news exposure is assumed to have stronger effects on political outcome variables like participation and knowledge than first-level incidental news exposure. The Political Incidental News Exposure Model further acknowledges intention-based (i.e., incidental news exposure while not looking for political news) and topic-based incidental news exposure (i.e., incidental news exposure while looking for other political news) and it conceptualizes incidental news exposure with respect to political and non-political content. Theoretical and methodological implications are discussed.
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In the last two decades, communication research dedicated substantial attention to the effects of incidental exposure (IE) to political information. In this meta-analysis, we analyzed the relationship of IE and five outcomes relevant for democracies. Including 106 distinct samples with more than 100,000 respondents, we observed positive cross-sectional relationships between IE and news use, political knowledge, political participation, expressive engagement, and political discussion. These effects shrink substantially but remain significant for panel studies. While we found a stronger relationship with knowledge for experiments compared to surveys, the relationship between IE and discussion and participation was not significant for experiments. Overall, findings suggest that IE matters, but its effects are smaller and more nuanced than previously thought. Also, the effects of IE are strongest when there is congruence between the exposure setting and the outcome setting. We discuss theoretical and methodological implications for IE research and the field at large.
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This study investigates antecedents and consequences of incidental and intentional exposure behavior to political information on social media. Based on the Social Media Political Participation Model (SMPPM), we investigated how political and non-political motivations predict intentional and incidental exposure modes while accounting for moderators (i.e., personal curation skills and the frequency of social media political exposure). We also examined how intentional and incidental exposure modes affect low- and high-effort political participation. We rely on data from a two-wave panel survey based on representative quotas for the Austrian population (N = 559) to run autoregressive models. Political information motivation predicted the intentional mode, and this relationship was stronger with rising levels of curation skills. By contrast, entertainment and social interaction motivations increased individuals’ incidental exposure mode. The intentional mode led to low-effort political participation but not to high-effort participation. However, the incidental mode was unrelated to both low- and high-effort participation.
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This article argues for new approaches to the study of incidental exposure that better account for the role of algorithms, platforms, and processes of datafication in shaping the likelihood of news exposure online. It offers a critique of three themes prominent in the incidental exposure literature: (1) incidental exposure connotes accidental exposure to news on social media, (2) news content is ubiquitous on social media, and (3) incidental exposure can be conceptually distinguished from intentional exposure to news on social media. This article proposes a new metaphor to reframe research on incidental exposure: ‘attraction’ to news.
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We assess whether and how accidental exposure to political information on social media contributes to citizens’ online political participation in comparative perspective. Based on three online surveys of samples representative of German, Italian, and British Internet users in the aftermath of the 2014 European Parliament elections, we find that accidental exposure to political information on social media is positively and significantly correlated with online participation in all three countries, particularly so in Germany where overall levels of participation were lower. We also find that interest in politics moderates this relationship so that the correlation is stronger among the less interested than among the highly interested. These findings suggest that inadvertent encounters with political content on social media are likely to reduce the gap in online engagement between citizens with high and low interest in politics, potentially broadening the range of voices that make themselves heard.
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\n The profusion of information about current events in digital media makes it likely that individuals are exposed to news through the course of everyday life, even when they are not motivated to do so. Yet, such incidental news exposure and its consequences depend on a multitude of characteristics that are unique to individuals and the social and information environments they inhabit. This complexity makes it difficult to evaluate the broader democratic implications of incidental exposure. To address this challenge, we propose an ecological model that offers a more comprehensive framework for theorizing and studying incidental news exposure in digital media environments. The model organizes factors influencing incidental exposure into six ecological levels that span individual and environmental domains. It further distinguishes state-like factors (i.e. malleable, context-dependent) and trait-like factors (i.e. stable, context-independent). We demonstrate how the model can (1) better define types of incidental exposure, (2) theorize how factors can\n interact\n across levels to shape exposure and its consequences, and (3) identify promising areas for future research.\n
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\n Concerns persist over the potential for the fragmented media environment to promote motivation-based political knowledge gaps between those who are interested in politics and those who are not. Yet, there is also evidence that the Internet can provide opportunities for individuals to incidentally encounter and learn from news, which may decrease these knowledge gaps. The current study tests this possibility using two, two-wave panel surveys of adults in the United States conducted during the 2012 and 2016 presidential elections. Across two distinct electoral contexts, we find evidence that incidental exposure to online news and political information promotes learning about presidential candidates’ policy positions over the course of the campaign. In addition, the data suggest the\n least\n politically interested benefit the most from this incidental exposure, as they see the largest gains in political knowledge. These findings indicate that opportunities to learn via incidental exposure have the potential to reduce motivation-based knowledge gaps.\n
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Research on incidental news exposure in the context of social media focuses on ‘successful’ incidental news exposure – when unintended news contacts result in active engagement and knowledge gains. However, we lack both theoretical and empirical approaches to the far more likely case that people keep on scrolling through their newsfeed without any post triggering active engagement. To fill this gap, the article conceptualizes a triple-path model of incidental news exposure on social media as a process. Building upon the Cognitive Mediation Model, dual system theories on information processing and recent empirical findings, three different pathways of incidental news processing are identified: automatic, incidental and active. The triple-path model thus allows to theorize the learning potentials that can plausibly be expected from each incidental news exposure path as a starting point for future research.
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