Hashtag Segmentation

Hashtag segmentation, the task of splitting hashtags into their constituent words or phrases, is crucial for effectively analyzing social media data. Research focuses on developing robust models, often leveraging weakly supervised learning techniques and large-scale datasets, to overcome challenges posed by the diverse and often creatively written nature of hashtags. These advancements improve the accuracy of downstream tasks like sentiment analysis and hate speech detection, particularly in multilingual contexts, where zero-shot approaches are showing promise. The development of more comprehensive and diverse benchmark datasets is also a key area of ongoing work, aiming to create more reliable evaluations of model performance.