Emotions and virality
Social transmission of political messages on Twitter
Bibliographic Data
| ID | 7532858 |
|---|---|
| Authors | Niklas Pivecka (0000-0001-7844-7118, University of Vienna, corresponding author), Roja Alexandra Ratzinger (0000-0003-2163-104X, Johannes Kepler University of Linz), Arnd Florack (0000-0001-9906-0043, University of Vienna) |
| Year | 2022 |
| Volume | 13 |
| Pages | 931921-931921 |
| Publication date | 2022-11-11 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychology (JOURNAL) |
| Journal identifiers | ISSN: 1664-1078 • E-ISSN: 1664-1078 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyg.2022.931921 |
| PMID | 36438335 |
| OpenAlex | W4308937911 |
| Language | EN |
| Citations received | 3 |
| References cited | 51 |
Drawing on previous literature that valence and arousal constitute the fundamental properties of emotions and that emotional content is a determinant of social transmission, this study examines the role of valence and arousal in the social transmission of politicians' messages on Twitter. For over 3,000 tweets from five Austrian party leaders, the discrete emotion that the message intended to elicit in its recipients was captured by human coders and then classified on its valence (positive or negative) and arousal (low or high). We examined the effects of valence and arousal on the retweet probability of messages. Results indicate that tweets eliciting a negative (vs. positive) valence decreased retweet probability, whereas tweets eliciting a high (vs. low) arousal increased retweet probability. The present research replicates previous findings that arousal constitutes a determinant of social transmission but extends this mechanism to the realm of political communication on Twitter. Moreover, in contrast to the frequently mentioned negativity bias, positive emotions increased the likelihood of a message being shared in this study
Arousal · Cognition · Cognitive psychology · Emotional valence · Low arousal theory · Negativity bias · Negativity effect · Realm · Valence (chemistry · Chemistry · Misinformation and Its Impacts · Neuroscience · Opinion Dynamics and Social Influence · Psychology · Social Media and Politics · Social Psychology
Selection and Transmission Processes for Information in the Emerging Media Environment
Are They Talking to Me? Cognitive and Affective Effects of Interactivity in Politicians' Twitter Communication
Stimulus Sampling and Social Psychological Experimentation
Confirmation Bias, Ingroup Bias, and Negativity Bias in Selective Exposure to Political Information
Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network
Arousal Increases Social Transmission of Information
Measuring emotion
Fitting Linear Mixed-Effects Models Using lme4
Social Sharing of Emotion During the Covid-19 Pandemic
The Effects of Negativity and Motivated Information Processing During a Political Campaign
The immutability of valence and arousal in the foundation of emotion
Twitter use in election campaigns
Negative emotions shape the diffusion of cancer tweets
Investigating Variation in Replicability
The sky is falling
News, Politics, and Negativity
Election Campaigning on Social Media
Independence and bipolarity in the structure of current affect
A circumplex model of affect
Bad is Stronger than Good
A Sadness Bias in Political News Sharing? The Role of Discrete Emotions in the Engagement and Dissemination of Political News on Facebook
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |