Detecting Online Risks and Supportive Interaction in Instant Messenger Conversations using Czech Transformers
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| Year of publication | 2021 |
| Type | Article in Proceedings |
| Conference | Recent Advances in Slavonic Natural Language Processing (RASLAN 2021) |
| MU Faculty or unit | |
| Citation | |
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| Keywords | Online Risks; Supportive Interaction; Facebook Messenger; Text Classification |
| Description | We present a comparison of state-of-the-art models for text clas- sification of Online Risks and Supportive Interaction in anonymized In- stant Messenger conversations held in Czech. We compare the transformer models Czert, RobeCzech, and FERNET-C5 with the Fasttext classifier as a baseline. For the comparison, we build a novel dataset with five sub- categories for the Online Risks and five for the Supportive Interaction. We solve the balanced classification problem achieving 75.44 - 89.66 F1 score depending on the category. Our results show that the transformer models perform consistently better than the baseline. |
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