# The Grievance Dictionary: Understanding Threatening Language Use

arXiv: https://arxiv.org/abs/2009.04798 · HTML: https://mlsanity.com/paper/2009.04798/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Sep 2020.

## Built on by (most cited first, 7 of 7)

- [Dictionary-Assisted Supervised Contrastive Learning](https://mlsanity.com/paper/2210.15172/) (2022)
- [Misinformation is not about Bad Facts: An Analysis of the Production and Consumption of Fringe Content](https://mlsanity.com/paper/2403.08391/) (2024)
- [Translating the Grievance Dictionary: a psychometric evaluation of Dutch, German, and Italian versions](https://mlsanity.com/paper/2505.07495/) (2025)
- [Themes of Revenge: Automatic Identification of Vengeful Content in Textual Data](https://mlsanity.com/paper/2205.01731/) (2022)
- [Unifying the Extremes: Developing a Unified Model for Detecting and Predicting Extremist Traits and Radicalization](https://mlsanity.com/paper/2501.04820/) (2025)
- [Examining the Role of YouTube Production and Consumption Dynamics on the Formation of Extreme Ideologies](https://mlsanity.com/paper/2603.08049/) (2026)
- [From a Word-Level Dictionary to Sentence-Level Semantics: Multilingual Grievance Labelling with Contextual Models](https://mlsanity.com/paper/2607.20946/) (2026)

## Abstract (arXiv)

This paper introduces the Grievance Dictionary, a psycholinguistic dictionary which can be used to automatically understand language use in the context of grievance-fuelled violence threat assessment. We describe the development the dictionary, which was informed by suggestions from experienced threat assessment practitioners. These suggestions and subsequent human and computational word list generation resulted in a dictionary of 20,502 words annotated by 2,318 participants. The dictionary was validated by applying it to texts written by violent and non-violent individuals, showing strong evidence for a difference between populations in several dictionary categories. Further classification tasks showed promising performance, but future improvements are still needed. Finally, we provide instructions and suggestions for the use of the Grievance Dictionary by security professionals and (violence) researchers.