Emotion, Motivation, and the Persuasive Effects of Message Framing

Yan, Changmin; Dillard, James Price; Shen, Fuyuan

doi:10.1111/j.1460-2466.2012.01655.x

Cited by 50 publications

(39 citation statements)

References 46 publications

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“…The popularity of the morality frame, in turn, was explained by some participants from an impression‐management motivation, with users trying to communicate a specific identity to others. These results are consistent with another strand of framing theory, which connects the effects of message frames to specific motivations (e.g., Yan, Dillard, & Shen, ). Thus, in addition to—or, perhaps, in combination with—producing specific emotional responses, frames may activate specific motivations related to news sharing.…”

Section: Discussionsupporting

confidence: 89%

Behavioral Effects of Framing on Social Media Users: How Conflict, Economic, Human Interest, and Morality Frames Drive News Sharing

2017

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We hypothesize that generic frames influence what news people share on Facebook and Twitter through three different routes: emotions, motivations, and psychological engagement. Using a mixed-methods design, a content analysis of a representative sample of articles published in six Chilean outlets was combined with in-depth interviews with digital journalists. After controlling for issue, newsworthiness, informational utility, valence, and other confounds, results show that-across platforms-a morality frame increases news sharing, whereas a conflict frame decreases it. Emphasizing economic consequences also decreases sharing, but only on Facebook. Surprisingly, the human interest angle has no noticeable effects. These results show that news frames can have behavioral consequences, and confirm the existence of a gap between preferred frames of journalists and users.

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Section: Discussionsupporting

confidence: 89%

Behavioral Effects of Framing on Social Media Users: How Conflict, Economic, Human Interest, and Morality Frames Drive News Sharing

2017

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Section: Discussionmentioning

confidence: 99%

“…Recent work by Yan, Dillard, and Shen (2012) has shown that emotional stimuli can activate the approach and avoidance system and that these changes in approach and avoidance activity in turn moderate the effects of framed messages. In fact, there may be several factors that can influence the effects of message framing through their effects on the approach and avoidance systems (Yan et al, 2012). As Rothman and colleagues (2006) have pointed out, investigating the extent to which factors external to the message can influence recipients’ approach and avoidance systems and thereby the effectiveness of gain- and loss-framed messages is a particularly promising avenue for message framing research.…”

Section: Discussionmentioning

confidence: 99%

Does perceived risk influence the effects of message framing? A new investigation of a widely held notion

Riet

Cox

et al. 2014

Psychology & Health

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Health-promoting messages can be framed in terms of the beneficial consequences of healthy behaviour (gain-framed messages) or the detrimental consequences of unhealthy behaviour (loss-framed messages). An influential notion holds that the perceived risk associated with the recommended behaviour determines the relative persuasiveness of gain- and loss-framed messages. This ‘risk-framing hypothesis’, as we call it, was derived from prospect theory, has been central to health message framing research for the last two decades, and does not cease to appeal to researchers. The present paper examines the validity of the risk-framing hypothesis. We performed six empirical studies on the interaction between perceived risk and message framing. These studies were conducted in two different countries and employed framed messages targeting skin cancer prevention and detection, physical activity, breast self-examination and vaccination behaviour. Behavioural intention served as the outcome measure. None of these studies found evidence in support of the risk-framing hypothesis. We conclude that the empirical evidence in favour of the hypothesis is weak and discuss the ramifications of this for future message framing research.

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“…While we distinguished among political ideology and candidate preference, this study has for example not analyzed differences in psychological characteristics of users. Research in the field of message framing has shown that people's motivations are subject to individual variations that will cause them to experience emotionally evocative message as a function of those individual differences (Yan, Dillard, & Shen, 2012). Second, while we controlled for the initial condition of videos on YouTube, we did include a separate control group in this analysis.…”

Section: Discussionmentioning

confidence: 99%

Communicating with Algorithms: A Transfer Entropy Analysis of Emotions-based Escapes from Online Echo Chambers

Hilbert

Ahmed

Cho

et al. 2018

Communication Methods and Measures

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Online algorithms have received much blame for polarizing emotions during the 2016 U.S. Presidential election. We use transfer entropy to measure directed information flows from human emotions to YouTube's video recommendation engine, and back, from recommended videos to users' emotions. We find that algorithmic recommendations communicate a statistically significant amount of positive and negative affect to humans. Joy is prevalent in emotional polarization, while sadness and fear play significant roles in emotional convergence. These findings can help to design more socially responsible algorithms by starting to focus on the emotional content of algorithmic recommendations. Employing a computational-experimental mixed method approach, the study serves as a demonstration of how the mathematical theory of communication can be used both to quantify human-machine communication, and to test hypotheses in the social sciences. Communicating with algorithms. 2 Communicating with algorithms: A transfer entropy analysis of emotions-based escapes from online echo chambers Algorithms intermediate almost all of the roughly 3.5 hours per day that each American communicates online (Center for the Digital Future, 2016). Algorithms decide how fast information is transferred and what information is presented (Hannak et al., 2013; Lazer, 2015). The proactive role of algorithms in communication processes can be conceptualized as an active dialogue between users and algorithms. Users communicate preferences (advertently or not), which are interpreted by algorithms (e.g., by recommender engines or bots), which then send responses back to users, who receive, interpret, and react to the algorithmic reply. In this study, we quantify the flow of information in the conceptual communication channel between users and socially responsive algorithms. Particularly, we first demonstrate that human emotions (joy, fear, sadness, etc.) are communicated to the selection mechanism of videos recommended by YouTube (via an individuals' choice of search terms), and second that the video's emotions influence how the viewer feels after being exposed to the videos. We study emotions related to Presidential candidates from the 2016 U.S. election. Rather than making assumptions about how recommender systems work, we systematically manipulate YouTube's real-world recommender system to create stimuli in a mixed-method computational-experimental approach. Algorithmic Filter Bubbles and Echo Chambers In the two-step communication between algorithms and humans it is common (but by no means obligatory) that the algorithm takes on the role of a confirmatory communication partner that reassures and often reinforces received information through positive feedback. This leads to the notorious "filter bubbles" (Pariser, 2011). The separation of users from contradictory information also gathers likeminded people in similar communication spaces, which then creates reinforcing echo chambers (

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Emotion, Motivation, and the Persuasive Effects of Message Framing

Cited by 50 publications

References 46 publications

Behavioral Effects of Framing on Social Media Users: How Conflict, Economic, Human Interest, and Morality Frames Drive News Sharing

Behavioral Effects of Framing on Social Media Users: How Conflict, Economic, Human Interest, and Morality Frames Drive News Sharing

Does perceived risk influence the effects of message framing? A new investigation of a widely held notion

Communicating with Algorithms: A Transfer Entropy Analysis of Emotions-based Escapes from Online Echo Chambers

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