# Aggression-annotated Corpus of Hindi-English Code-mixed Data

arXiv: https://arxiv.org/abs/1803.09402 · HTML: https://mlsanity.com/paper/1803.09402/

## Key facts

- Cited by 40 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Mar 2018.

## Built on by (most cited first, 30 of 40)

- [Towards generalisable hate speech detection: a review on obstacles and solutions](https://mlsanity.com/paper/2102.08886/) (2021)
- [The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges](https://mlsanity.com/paper/2212.09660/) (2022)
- [A systematic review of Hate Speech automatic detection using Natural Language Processing](https://mlsanity.com/paper/2106.00742/) (2021)
- [MetaHate: A Dataset for Unifying Efforts on Hate Speech Detection](https://mlsanity.com/paper/2401.06526/) (2024)
- [Memotion 3: Dataset on Sentiment and Emotion Analysis of Codemixed Hindi-English Memes](https://mlsanity.com/paper/2303.09892/) (2023)
- [An Information Retrieval Approach to Building Datasets for Hate Speech Detection](https://mlsanity.com/paper/2106.09775/) (2021)
- [Uncovering Political Hate Speech During Indian Election Campaign: A New Low-Resource Dataset and Baselines](https://mlsanity.com/paper/2306.14764/) (2023)
- [Hater-O-Genius Aggression Classification using Capsule Networks](https://mlsanity.com/paper/2105.11219/) (2021)
- ["Define Your Terms" : Enhancing Efficient Offensive Speech Classification with Definition](https://mlsanity.com/paper/2402.03221/) (2024)
- [A Comprehensive Study on NLP Data Augmentation for Hate Speech Detection: Legacy Methods, BERT, and LLMs](https://mlsanity.com/paper/2404.00303/) (2024)
- [COMI-LINGUA: Expert Annotated Large-Scale Dataset for Multitask NLP in Hindi-English Code-Mixing](https://mlsanity.com/paper/2503.21670/) (2025)
- [Down the Rabbit Hole: Detecting Online Extremism, Radicalisation, and Politicised Hate Speech](https://mlsanity.com/paper/2301.11579/) (2023)
- [OffMix-3L: A Novel Code-Mixed Dataset in Bangla-English-Hindi for Offensive Language Identification](https://mlsanity.com/paper/2310.18387/) (2023)
- [Challenges and Considerations with Code-Mixed NLP for Multilingual Societies](https://mlsanity.com/paper/2106.07823/) (2021)
- [The ComMA Dataset V0.2: Annotating Aggression and Bias in Multilingual Social Media Discourse](https://mlsanity.com/paper/2111.10390/) (2021)
- [Ceasing hate withMoH: Hate Speech Detection in Hindi-English Code-Switched Language](https://mlsanity.com/paper/2110.09393/) (2021)
- [Highly Generalizable Models for Multilingual Hate Speech Detection](https://mlsanity.com/paper/2201.11294/) (2022)
- [The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages](https://mlsanity.com/paper/2310.14557/) (2023)
- [The Uli Dataset: An Exercise in Experience Led Annotation of oGBV](https://mlsanity.com/paper/2311.09086/) (2023)
- [Explain Thyself Bully: Sentiment Aided Cyberbullying Detection with Explanation](https://mlsanity.com/paper/2401.09023/) (2024)
- [SS-BERT: Mitigating Identity Terms Bias in Toxic Comment Classification by Utilising the Notion of "Subjectivity" and "Identity Terms"](https://mlsanity.com/paper/2109.02691/) (2021)
- [Offensive Language Detection with BERT-based models, By Customizing Attention Probabilities](https://mlsanity.com/paper/2110.05133/) (2021)
- [Nipping in the Bud: Detection, Diffusion and Mitigation of Hate Speech on Social Media](https://mlsanity.com/paper/2201.00961/) (2022)
- [SOLD: Sinhala Offensive Language Dataset](https://mlsanity.com/paper/2212.00851/) (2022)
- [Cross-lingual Offensive Language Detection: A Systematic Review of Datasets, Transfer Approaches and Challenges](https://mlsanity.com/paper/2401.09244/) (2024)
- [A Multi-faceted Semi-Synthetic Dataset for Automated Cyberbullying Detection](https://mlsanity.com/paper/2402.10231/) (2024)
- [Improving code-mixed hate detection by native sample mixing: A case study for Hindi-English code-mixed scenario](https://mlsanity.com/paper/2405.20755/) (2024)
- [Studying Socially Unacceptable Discourse Classification (SUD) through different eyes: "Are we on the same page ?"](https://mlsanity.com/paper/2308.04180/) (2023)
- [HarmPot: An Annotation Framework for Evaluating Offline Harm Potential of Social Media Text](https://mlsanity.com/paper/2403.11108/) (2024)
- [A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings](https://mlsanity.com/paper/2505.12116/) (2025)

## Abstract (arXiv)

As the interaction over the web has increased, incidents of aggression and related events like trolling, cyberbullying, flaming, hate speech, etc. too have increased manifold across the globe. While most of these behaviour like bullying or hate speech have predated the Internet, the reach and extent of the Internet has given these an unprecedented power and influence to affect the lives of billions of people. So it is of utmost significance and importance that some preventive measures be taken to provide safeguard to the people using the web such that the web remains a viable medium of communication and connection, in general. In this paper, we discuss the development of an aggression tagset and an annotated corpus of Hindi-English code-mixed data from two of the most popular social networking and social media platforms in India, Twitter and Facebook. The corpus is annotated using a hierarchical tagset of 3 top-level tags and 10 level 2 tags. The final dataset contains approximately 18k tweets and 21k facebook comments and is being released for further research in the field.