mlsanityData to 14 Oct 2026

MBTI Personality Prediction for Fictional Characters Using Movie Scripts

arXiv 2210.10994 ↗First posted 20 Oct 2022cs.AI cs.CL cs.LGcited by 14

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Abstract (arXiv)

An NLP model that understands stories should be able to understand the characters in them. To support the development of neural models for this purpose, we construct a benchmark, Story2Personality. The task is to predict a movie character's MBTI or Big 5 personality types based on the narratives of the character. Experiments show that our task is challenging for the existing text classification models, as none is able to largely outperform random guesses. We further proposed a multi-view model for personality prediction using both verbal and non-verbal descriptions, which gives improvement compared to using only verbal descriptions. The uniqueness and challenges in our dataset call for the development of narrative comprehension techniques from the perspective of understanding characters.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 14 of its 45 references that are in the map. First posted on arXiv 20 Oct 2022.

Builds on

14 of 45 references.

References · 14

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,210
  4. 2017The NarrativeQA Reading Comprehension Challengecited by 597
  5. 2019Learning to Speak and Act in a Fantasy Text Adventure Gamecited by 122
  6. 2022Fantastic Questions and Where to Find Them: FairytaleQA -- An Authentic Dataset for Narrative Comprehensioncited by 80
  7. 2021"Let Your Characters Tell Their Story": A Dataset for Character-Centric Narrative Understandingcited by 48
  8. 2022Educational Question Generation of Children Storybooks via Question Type Distribution Learning and Event-Centric Summarizationcited by 26
  9. 2019Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characterscited by 23
  10. 2022TVShowGuess: Character Comprehension in Stories as Speaker Guessingcited by 17
  11. 2015Inferring Interpersonal Relations in Narrative Summariescited by 16
  12. 2022A Survey of Machine Narrative Reading Comprehension Assessmentscited by 10
2 more
  1. 2015Annotating Character Relationships in Literary Textscited by 7
  2. 2022NECE: Narrative Event Chain Extraction Toolkitcited by 2

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Citing papers per year: 2022: 1; 2023: 4; 2024: 7; 2025: 2.

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  1. 2023RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generationcited by 25
  2. 2023Editing Personality for Large Language Modelscited by 22
  3. 2023Personality Understanding of Fictional Characters during Book Readingcited by 20
  4. 2022Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mindcited by 19
  5. 2024Mitigating Hallucination in Fictional Character Role-Playcited by 18
  6. 2024CHIRON: Rich Character Representations in Long-Form Narrativescited by 9
  7. 2024EERPD: Leveraging Emotion and Emotion Regulation for Improving Personality Detectioncited by 7
  8. 2024Revealing Personality Traits: A New Benchmark Dataset for Explainable Personality Recognition on Dialoguescited by 7
  9. 2025Dynamic Context Adaptation for Consistent Role-Playing Agents with Retrieval-Augmented Generationscited by 4
  10. 2024BookWorm: A Dataset for Character Description and Analysiscited by 3
  11. 2023Personality-aware Human-centric Multimodal Reasoning: A New Task, Dataset and Baselinescited by 2
  12. 2024CHATTER: A Character Attribution Dataset for Narrative Understandingcited by 2
2 more
  1. 2024Is Personality Prediction Possible Based on Reddit Comments?cited by 0
  2. 2025Integrating Video and Text: A Balanced Approach to Multimodal Summary Generation and Evaluationcited by 0