---
language:
- ru

tags:
- toxic comments classification

licenses:
- cc-by-nc-sa
---

## General concept of the model

This model is trained on the dataset of sensitive topics of the Russian language. The concept of sensitive topics is described [in this article ](https://arxiv.org/abs/2103.05345) presented at the workshop for Balto-Slavic NLP at the EACL-2021 conference. Please note that this article describes the first version of the dataset, while the model is trained on the extended version of the dataset open-sourced on our [GitHub](https://github.com/skoltech-nlp/inappropriate-sensitive-topics/blob/main/Version2/sensitive_topics/sensitive_topics.csv). The properties of the dataset is the same as the one described in the article, the only difference is the size.


## Instructions

The model predicts combinations of 18 sensitive topics described in the [article](https://arxiv.org/abs/2103.05345). You can find step-by-step instructions for using the model [here](https://github.com/skoltech-nlp/inappropriate-sensitive-topics/blob/main/Version2/sensitive_topics/Inference.ipynb)


## Metrics

The dataset partially manually labeled samples and partially semi-automatically labeled samples. Learn more in our article. We tested the performance of the classifier only on the part of manually labeled data that is why some topics are not well represented in the test set.


|                   | precision | recall | f1-score | support |
|-------------------|-----------|--------|----------|---------|
| offline_crime     |      0.65 |   0.55 |      0.6 |     132 |
| online_crime      |       0.5 |   0.46 |     0.48 |      37 |
| drugs             |      0.87 |    0.9 |     0.88 |      87 |
| gambling          |       0.5 |   0.67 |     0.57 |       6 |
| pornography       |      0.73 |   0.59 |     0.65 |     204 |
| prostitution      |      0.75 |   0.69 |     0.72 |      91 |
| slavery           |      0.72 |   0.72 |     0.73 |      40 |
| suicide           |      0.33 |   0.29 |     0.31 |       7 |
| terrorism         |      0.68 |   0.57 |     0.62 |      47 |
| weapons           |      0.89 |   0.83 |     0.86 |     138 |
| body_shaming      |       0.9 |   0.67 |     0.77 |     109 |
| health_shaming    |      0.84 |   0.55 |     0.66 |     108 |
| politics          |      0.68 |   0.54 |      0.6 |     241 |
| racism            |      0.81 |   0.59 |     0.68 |     204 |
| religion          |      0.94 |   0.72 |     0.81 |     102 |
| sexual_minorities |      0.69 |   0.46 |     0.55 |     102 |
| sexism            |      0.66 |   0.64 |     0.65 |     132 |
| social_injustice  |      0.56 |   0.37 |     0.45 |     181 |
| none              |      0.62 |   0.67 |     0.64 |     250 |
| micro avg         |      0.72 |   0.61 |     0.66 |    2218 |
| macro avg         |       0.7 |    0.6 |     0.64 |    2218 |
| weighted avg      |      0.73 |   0.61 |     0.66 |    2218 |
| samples avg       |      0.75 |   0.66 |     0.68 |    2218 |

## Licensing Information

[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png

## Citation

If you find this repository helpful, feel free to cite our publication:

```
@inproceedings{babakov-etal-2021-bsnlp,
    title = "Detecting Inappropriate Messages on Sensitive Topics that Could Harm a Company's Reputation",
    author = "Babakov, Nikolay and Logacheva, Varvara and Kozlova, Olga and Semenov, Nikita and Panchenko, Alexander",
    booktitle = "To appear in the Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
    month = April,
    year = "2021",
    address = "Kyiv, Ukraine"
}
```