# A Survey on Sentiment and Emotion Analysis for Computational Literary Studies

arXiv: https://arxiv.org/abs/1808.03137 · HTML: https://mlsanity.com/paper/1808.03137/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Aug 2018.

## Built on by (most cited first, 14 of 14)

- [Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions](https://mlsanity.com/paper/2403.01222/) (2024)
- [Emotion-Aware, Emotion-Agnostic, or Automatic: Corpus Creation Strategies to Obtain Cognitive Event Appraisal Annotations](https://mlsanity.com/paper/2102.12858/) (2021)
- [ViNTER: Image Narrative Generation with Emotion-Arc-Aware Transformer](https://mlsanity.com/paper/2202.07305/) (2022)
- [Modeling Emotional Trajectories in Written Stories Utilizing Transformers and Weakly-Supervised Learning](https://mlsanity.com/paper/2406.02251/) (2024)
- [Applications and Challenges of Sentiment Analysis in Real-life Scenarios](https://mlsanity.com/paper/2301.09912/) (2023)
- [An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3](https://mlsanity.com/paper/2506.00312/) (2025)
- [Artwork Interpretation with Vision Language Models: A Case Study on Emotions and Emotion Symbols](https://mlsanity.com/paper/2511.22929/) (2025)
- [Computational Storytelling and Emotions: A Survey](https://mlsanity.com/paper/2205.10967/) (2022)
- [Automatic Emotion Modelling in Written Stories](https://mlsanity.com/paper/2212.11382/) (2022)
- [Protagonists' Tagger in Literary Domain -- New Datasets and a Method for Person Entity Linkage](https://mlsanity.com/paper/2110.01349/) (2021)
- [Emotion detection of social data: APIs comparative study](https://mlsanity.com/paper/2207.10654/) (2022)
- [Affect as a proxy for literary mood](https://mlsanity.com/paper/2304.02894/) (2023)
- [Sentiment Analysis in Digital Spaces: An Overview of Reviews](https://mlsanity.com/paper/2310.19687/) (2023)
- [LitSeg: Narrative-Aware Document Segmentation for Literary RAG](https://mlsanity.com/paper/2605.27156/) (2026)

## Abstract (arXiv)

Emotions are a crucial part of compelling narratives: literature tells us about people with goals, desires, passions, and intentions. Emotion analysis is part of the broader and larger field of sentiment analysis, and receives increasing attention in literary studies. In the past, the affective dimension of literature was mainly studied in the context of literary hermeneutics. However, with the emergence of the research field known as Digital Humanities (DH), some studies of emotions in a literary context have taken a computational turn. Given the fact that DH is still being formed as a field, this direction of research can be rendered relatively new. In this survey, we offer an overview of the existing body of research on emotion analysis as applied to literature. The research under review deals with a variety of topics including tracking dramatic changes of a plot development, network analysis of a literary text, and understanding the emotionality of texts, among other topics.