An Incremental Clustering Baseline for Event Detection on Twitter
This provides a relevant baseline for future research in event detection on social media, though it appears incremental.
The paper tackles event detection in Twitter text streams by using incremental clustering with sentence embeddings, achieving significant improvements compared to previous studies.
Event detection in text streams is a crucial task for the analysis of online media and social networks. One of the current challenges in this field is establishing a performance standard while maintaining an acceptable level of computational complexity. In our study, we use an incremental clustering algorithm combined with recent advancements in sentence embeddings. Our objective is to compare our findings with previous studies, specifically those by Cao et al. (2024) and Mazoyer et al. (2020). Our results demonstrate significant improvements and could serve as a relevant baseline for future research in this area.