# GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception

arXiv: https://arxiv.org/abs/1912.03184 · HTML: https://mlsanity.com/paper/1912.03184/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Dec 2019.

## Built on by (most cited first, 30 of 37)

- [Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction](https://mlsanity.com/paper/2206.05238/) (2022)
- [Multimodal Emotion-Cause Pair Extraction in Conversations](https://mlsanity.com/paper/2110.08020/) (2021)
- [Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions](https://mlsanity.com/paper/2403.01222/) (2024)
- [Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corpora](https://mlsanity.com/paper/2209.06701/) (2022)
- [SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations](https://mlsanity.com/paper/2405.13049/) (2024)
- [Machine-in-the-Loop Rewriting for Creative Image Captioning](https://mlsanity.com/paper/2111.04193/) (2021)
- [Both Matter: Enhancing the Emotional Intelligence of Large Language Models without Compromising the General Intelligence](https://mlsanity.com/paper/2402.10073/) (2024)
- [News Headline Grouping as a Challenging NLU Task](https://mlsanity.com/paper/2105.05391/) (2021)
- [Multi-Task Learning and Adapted Knowledge Models for Emotion-Cause Extraction](https://mlsanity.com/paper/2106.09790/) (2021)
- [x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations](https://mlsanity.com/paper/2203.10909/) (2022)
- [Emotion Recognition based on Psychological Components in Guided Narratives for Emotion Regulation](https://mlsanity.com/paper/2305.10446/) (2023)
- [Where are We in Event-centric Emotion Analysis? Bridging Emotion Role Labeling and Appraisal-based Approaches](https://mlsanity.com/paper/2309.02092/) (2023)
- [Unlocking LLMs: Addressing Scarce Data and Bias Challenges in Mental Health](https://mlsanity.com/paper/2412.12981/) (2024)
- [Emotion Stimulus Detection in German News Headlines](https://mlsanity.com/paper/2107.12920/) (2021)
- [Experiencer-Specific Emotion and Appraisal Prediction](https://mlsanity.com/paper/2210.12078/) (2022)
- [MAGPIE: Multi-Task Media-Bias Analysis Generalization for Pre-Trained Identification of Expressions](https://mlsanity.com/paper/2403.07910/) (2024)
- [Improving Language Models for Emotion Analysis: Insights from Cognitive Science](https://mlsanity.com/paper/2406.10265/) (2024)
- [iNews: A Multimodal Dataset for Modeling Personalized Affective Responses to News](https://mlsanity.com/paper/2503.03335/) (2025)
- ["Only ChatGPT gets me": An Empirical Analysis of GPT versus other Large Language Models for Emotion Detection in Text](https://mlsanity.com/paper/2503.04831/) (2025)
- [Emotionally Charged, Logically Blurred: AI-driven Emotional Framing Impairs Human Fallacy Detection](https://mlsanity.com/paper/2510.09695/) (2025)
- ["splink" is happy and "phrouth" is scary: Emotion Intensity Analysis for Nonsense Words](https://mlsanity.com/paper/2202.12132/) (2022)
- [Personality-aware Human-centric Multimodal Reasoning: A New Task, Dataset and Baselines](https://mlsanity.com/paper/2304.02313/) (2023)
- [Emotion Classification in Low and Moderate Resource Languages](https://mlsanity.com/paper/2402.18424/) (2024)
- [Cross-Register Projection for Headline Part of Speech Tagging](https://mlsanity.com/paper/2109.07483/) (2021)
- [On the Complementarity of Images and Text for the Expression of Emotions in Social Media](https://mlsanity.com/paper/2202.07427/) (2022)
- [Expressions Causing Differences in Emotion Recognition in Social Networking Service Documents](https://mlsanity.com/paper/2208.14244/) (2022)
- [Automatic Emotion Experiencer Recognition](https://mlsanity.com/paper/2305.16731/) (2023)
- [Detecting harassment and defamation in cyberbullying with emotion-adaptive training](https://mlsanity.com/paper/2501.16925/) (2025)
- [EmoNews: A Spoken Dialogue System for Expressive News Conversations](https://mlsanity.com/paper/2506.13894/) (2025)
- [Extending a Parliamentary Corpus with MPs' Tweets: Automatic Annotation and Evaluation Using MultiParTweet](https://mlsanity.com/paper/2512.11567/) (2025)

## Abstract (arXiv)

Most research on emotion analysis from text focuses on the task of emotion classification or emotion intensity regression. Fewer works address emotions as a phenomenon to be tackled with structured learning, which can be explained by the lack of relevant datasets. We fill this gap by releasing a dataset of 5000 English news headlines annotated via crowdsourcing with their associated emotions, the corresponding emotion experiencers and textual cues, related emotion causes and targets, as well as the reader's perception of the emotion of the headline. This annotation task is comparably challenging, given the large number of classes and roles to be identified. We therefore propose a multiphase annotation procedure in which we first find relevant instances with emotional content and then annotate the more fine-grained aspects. Finally, we develop a baseline for the task of automatic prediction of semantic role structures and discuss the results. The corpus we release enables further research on emotion classification, emotion intensity prediction, emotion cause detection, and supports further qualitative studies.