Semih Yagcioglu, Mehmet Saygin Seyfioglu, Begum Citamak, Batuhan Bardak, Seren Guldamlasioglu, Azmi Yuksel, Emin Islam Tatli
| Challenge: | Using domain-specific word embeddings, we propose a method to detect cyber security events from noisy short text. |
| Approach: | They propose a method that leverages domain-specific word embeddings and task-specific features to detect cyber security events from tweets. |
| Outcome: | The proposed model outperforms both baselines and traditional models on a dataset of 2K tweets and manually annotates them. |
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| Challenge: | Recent work on event detection from tweets has focused on localized events or breaking news only. |
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A French Corpus for Event Detection on Twitter (2020.lrec-1)
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| Challenge: | Existing datasets may have different definitions of event or topic, which leads to inconsistent results. |
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