# Deep Feelings: A Massive Cross-Lingual Study on the Relation between Emotions and Virality

arXiv: https://arxiv.org/abs/1503.04723 · HTML: https://mlsanity.com/paper/1503.04723/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Mar 2015.

## Built on by (most cited first, 2 of 2)

- [Uncovering the Limits of Text-based Emotion Detection](https://mlsanity.com/paper/2109.01900/) (2021)
- [REDAffectiveLM: Leveraging Affect Enriched Embedding and Transformer-based Neural Language Model for Readers' Emotion Detection](https://mlsanity.com/paper/2301.08995/) (2023)

## Abstract (arXiv)

This article provides a comprehensive investigation on the relations between virality of news articles and the emotions they are found to evoke. Virality, in our view, is a phenomenon with many facets, i.e. under this generic term several different effects of persuasive communication are comprised. By exploiting a high-coverage and bilingual corpus of documents containing metrics of their spread on social networks as well as a massive affective annotation provided by readers, we present a thorough analysis of the interplay between evoked emotions and viral facets. We highlight and discuss our findings in light of a cross-lingual approach: while we discover differences in evoked emotions and corresponding viral effects, we provide preliminary evidence of a generalized explanatory model rooted in the deep structure of emotions: the Valence-Arousal-Dominance (VAD) circumplex. We find that viral facets appear to be consistently affected by particular VAD configurations, and these configurations indicate a clear connection with distinct phenomena underlying persuasive communication.