| Challenge: | Emotion analysis in text is a field of research that encompasses a set of various natural language processing tasks. |
| Approach: | This tutorial provides an overview of research from emotion psychology . it discusses the use cases of emotion analysis in text, their societal impact and ethical considerations . |
| Outcome: | This paper provides an overview of research from emotion psychology which sets the ground for choosing adequate NLP methodology. |
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Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions (2024.lrec-main)
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| Challenge: | Emotion analysis (EA) is a rapidly growing field in natural language processing . there is no consensus on scope, direction, or methods for EA . |
| Approach: | They review 154 relevant NLP papers on emotion analysis from the last decade . they ask: how are EA tasks defined in NLP? what are the most prominent emotion frameworks and which emotions are modeled? |
| Outcome: | The authors examine 154 relevant NLP papers on emotion analysis from the last decade . they find that there is no consensus on scope, direction, or methods . |
Appraisal Theories for Emotion Classification in Text (2020.coling-main)
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| Challenge: | Automatic emotion categorization is based on textual units assigned to an emotion from a predefined inventory, for instance following the basic emotion classes proposed by Paul Ekman (1999) or Plutchik (2001). |
| Approach: | They propose to make automatic emotion categorization explicit by following theories of cognitive appraisal of events and show their potential for emotion classification when being encoded in classification models. |
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Who Feels What and Why? Annotation of a Literature Corpus with Semantic Roles of Emotions (C18-1)
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| Challenge: | Emotion analysis and classification is a challenging task which has been tackled with relatively straight-forward approaches. |
| Approach: | They propose to annotate emotion trigger phrases and entities in the roles of experiencers, targets, and causes of the emotion in literature by Project Gutenberg. |
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A Comprehensive Analysis of Preprocessing for Word Representation Learning in Affective Tasks (2020.acl-main)
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| Challenge: | Affective tasks such as sentiment analysis, emotion classification and sarcasm detection have enjoyed great popularity in recent years. |
| Approach: | They conduct a comprehensive analysis of the role of preprocessing techniques in affective analysis based on word vector models. |
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Interpretable Text Embeddings and Text Similarity Explanation: A Survey (2025.emnlp-main)
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| Challenge: | Text embeddings are a fundamental component in many NLP tasks, but their interpretation and explanation remain challenging. |
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A (Psycho-)Linguistically Motivated Scheme for Annotating and Exploring Emotions in a Genre-Diverse Corpus (2022.lrec-1)
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| Challenge: | Using a linguistic perspective, emotion annotation is considered a difficult task because of the lack of consensus on emotional categories, the fuzziness of boundaries between them or the great variability of emotion expressions types. |
| Approach: | They propose a scheme for emotion annotation and its manual application on a genre-diverse corpus of texts written in french. |
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From Text to Context: Contextualizing Language with Humans, Groups, and Communities for Socially Aware NLP (2024.naacl-tutorials)
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Adithya V Ganesan, Siddharth Mangalik, Vasudha Varadarajan, Nikita Soni, Swanie Juhng, João Sedoc, H. Andrew Schwartz, Salvatore Giorgi, Ryan L Boyd
| Challenge: | This tutorial will cover the latest techniques and libraries for doing so at each level of analysis. |
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An Emotional Mess! Deciding on a Framework for Building a Dutch Emotion-Annotated Corpus (2020.lrec-1)
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| Challenge: | Existing frameworks for emotion recognition are limited and do not allow for categorical versus dimensional oppositions. |
| Approach: | They propose to use the emotions joy, love, anger, sadness and fear as well as dimensional models to annotate texts from different domains and topics. |
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A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing (2022.findings-emnlp)
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| Challenge: | Empathy recognition and empathetic response generation tasks are well-established research directions, but there is little clarity on what empathy is and how it is being operationalized. |
| Approach: | They argue that current directions will benefit from a clear conceptualization that includes operationalizing cognitive empathy components. |
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An Analysis of Annotated Corpora for Emotion Classification in Text (C18-1)
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| Challenge: | Several datasets have been annotated and published for classification of emotions. |
| Approach: | They aggregated emotion corpora in a common file format with a shared annotation schema . they perform cross-corpus classification experiments to gain insight and a better understanding of differences . |
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