mlsanityData to 14 Oct 2026

Emotion Intensities in Tweets

arXiv 1708.03696 ↗First posted 11 Aug 2017cs.CLcited by 32

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Abstract (arXiv)

This paper examines the task of detecting intensity of emotion from text. We create the first datasets of tweets annotated for anger, fear, joy, and sadness intensities. We use a technique called best--worst scaling (BWS) that improves annotation consistency and obtains reliable fine-grained scores. We show that emotion-word hashtags often impact emotion intensity, usually conveying a more intense emotion. Finally, we create a benchmark regression system and conduct experiments to determine: which features are useful for detecting emotion intensity, and, the extent to which two emotions are similar in terms of how they manifest in language.

Key facts. Cited by 32 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Aug 2017.

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Citing papers per year: 2021: 6; 2022: 7; 2023: 5; 2024: 4; 2025: 4; 2026: 6.

32 papers.

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  1. 2022Fusing finetuned models for better pretrainingcited by 110
  2. 2023Knowledge is a Region in Weight Space for Fine-tuned Language Modelscited by 58
  3. 2022ColD Fusion: Collaborative Descent for Distributed Multitask Finetuningcited by 52
  4. 2021SpanEmo: Casting Multi-label Emotion Classification as Span-predictioncited by 37
  5. 2021Ruddit: Norms of Offensiveness for English Reddit Commentscited by 27
  6. 2022Where to start? Analyzing the potential value of intermediate modelscited by 23
  7. 2023''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Textcited by 15
  8. 2022Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corporacited by 13
  9. 2023ExpCLIP: Bridging Text and Facial Expressions via Semantic Alignmentcited by 13
  10. 2021Multi-Task Learning with Sentiment, Emotion, and Target Detection to Recognize Hate Speech and Offensive Languagecited by 12
  11. 2021Supporting Cognitive and Emotional Empathic Writing of Studentscited by 8
  12. 2024English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Promptscited by 7
20 more
  1. 2025Language Models Predict Empathy Gaps Between Social In-groups and Out-groupscited by 6
  2. 2021Emotion Stimulus Detection in German News Headlinescited by 4
  3. 2022Building a Dialogue Corpus Annotated with Expressed and Experienced Emotionscited by 4
  4. 2025Can Third-parties Read Our Emotions?cited by 4
  5. 2026SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA)cited by 4
  6. 2024"You are an expert annotator": Automatic Best-Worst-Scaling Annotations for Emotion Intensity Modelingcited by 3
  7. 2021EmoDNN: Understanding emotions from short texts through a deep neural network ensemblecited by 2
  8. 2022"splink" is happy and "phrouth" is scary: Emotion Intensity Analysis for Nonsense Wordscited by 2
  9. 2022Expressions Causing Differences in Emotion Recognition in Social Networking Service Documentscited by 1
  10. 2023Automatic Emotion Experiencer Recognitioncited by 1
  11. 2023Deep Model Compression Also Helps Models Capture Ambiguitycited by 1
  12. 2024Self-Knowledge Distillation for Learning Ambiguitycited by 1
  13. 2024Predicting Emotion Intensity in Polish Political Texts: Comparing Supervised Models and Large Language Models in a Resource-Poor Languagecited by 1
  14. 2025Understanding Mental Health Content on Social Media and Its Effect Towards Suicidal Ideationcited by 1
  15. 2026DimABSA: Building Multilingual and Multidomain Datasets for Dimensional Aspect-Based Sentiment Analysiscited by 1
  16. 2026Quality and Agreement in Multilabel Emotion Annotation: A Case Study and Evaluation Frameworkcited by 1
  17. 2025An Analytical Emotion Framework of Rumour Threads on Social Mediacited by 0
  18. 2026Reasoning under Ambiguity: Uncertainty-Aware Multilingual Emotion Classification under Partial Supervisioncited by 0
  19. 2026Some Emotions Run Deeper: Layer-wise Probing and Causal Intervention in Large Language Modelscited by 0
  20. 2026Emotion Experience, Expression, and Perception: Emotion Analysis on Multimodal Social Media Postscited by 0