# On Text-based Personality Computing: Challenges and Future Directions

arXiv: https://arxiv.org/abs/2212.06711 · HTML: https://mlsanity.com/paper/2212.06711/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 151 references that are in the map.
- First posted on arXiv 13 Dec 2022.

## Builds on (most cited first, 25 of 25)

- [A Survey on Bias and Fairness in Machine Learning](https://mlsanity.com/paper/1908.09635/) (2019)
- [Beyond Accuracy: Behavioral Testing of NLP models with CheckList](https://mlsanity.com/paper/2005.04118/) (2020)
- [Multi-Task Deep Neural Networks for Natural Language Understanding](https://mlsanity.com/paper/1901.11504/) (2019)
- [Measurement and Fairness](https://mlsanity.com/paper/1912.05511/) (2019)
- [Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models](https://mlsanity.com/paper/2110.07736/) (2021)
- [PANDORA Talks: Personality and Demographics on Reddit](https://mlsanity.com/paper/2004.04460/) (2020)
- [Investigating Audio, Visual, and Text Fusion Methods for End-to-End Automatic Personality Prediction](https://mlsanity.com/paper/1805.00705/) (2018)
- [The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions](https://mlsanity.com/paper/2004.13606/) (2020)
- [Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and Dimensionality](https://mlsanity.com/paper/2105.03484/) (2021)
- [Automatically Select Emotion for Response via Personality-affected Emotion Transition](https://mlsanity.com/paper/2106.15846/) (2021)
- [Assessing the Reliability of Word Embedding Gender Bias Measures](https://mlsanity.com/paper/2109.04732/) (2021)
- [Psycholinguistic Tripartite Graph Network for Personality Detection](https://mlsanity.com/paper/2106.04963/) (2021)
- [Pushing on Personality Detection from Verbal Behavior: A Transformer Meets Text Contours of Psycholinguistic Features](https://mlsanity.com/paper/2204.04629/) (2022)
- [A Language-independent and Compositional Model for Personality Trait Recognition from Short Texts](https://mlsanity.com/paper/1610.04345/) (2016)
- [25 Tweets to Know You: A New Model to Predict Personality with Social Media](https://mlsanity.com/paper/1704.05513/) (2017)
- [Evaluating the Construct Validity of Text Embeddings with Application to Survey Questions](https://mlsanity.com/paper/2202.09166/) (2022)
- [Items from Psychometric Tests as Training Data for Personality Profiling Models of Twitter Users](https://mlsanity.com/paper/2202.10415/) (2022)
- [Automatic Extraction of Personality from Text: Challenges and Opportunities](https://mlsanity.com/paper/1910.09916/) (2019)
- [Lexical-semantic resources: yet powerful resources for automatic personality classification](https://mlsanity.com/paper/1711.09824/) (2017)
- [Text-based automatic personality prediction: A bibliographic review](https://mlsanity.com/paper/2110.01186/) (2021)
- [Prompt-based System for Personality and Interpersonal Reactivity Prediction](https://mlsanity.com/paper/2203.12481/) (2022)
- [Personal-ITY: A Novel YouTube-based Corpus for Personality Prediction in Italian](https://mlsanity.com/paper/2011.05688/) (2020)
- [Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality](https://mlsanity.com/paper/2011.07009/) (2020)
- [Predicting Human Trustfulness from Facebook Language](https://mlsanity.com/paper/1808.05668/) (2018)
- [The Role of Time, Weather and Google Trends in Understanding and Predicting Web Survey Response](https://mlsanity.com/paper/2011.02034/) (2020)

## Built on by (most cited first, 3 of 3)

- [Enhancing Textual Personality Detection toward Social Media: Integrating Long-term and Short-term Perspectives](https://mlsanity.com/paper/2404.15067/) (2024)
- [Integrating Multi-view Analysis: Multi-view Mixture-of-Expert for Textual Personality Detection](https://mlsanity.com/paper/2408.08551/) (2024)
- [PRISM: A Personality-Driven Multi-Agent Framework for Social Media Simulation](https://mlsanity.com/paper/2512.19933/) (2025)

## Abstract (arXiv)

Text-based personality computing (TPC) has gained many research interests in NLP. In this paper, we describe 15 challenges that we consider deserving the attention of the research community. These challenges are organized by the following topics: personality taxonomies, measurement quality, datasets, performance evaluation, modelling choices, as well as ethics and fairness. When addressing each challenge, not only do we combine perspectives from both NLP and social sciences, but also offer concrete suggestions. We hope to inspire more valid and reliable TPC research.