As discussed in the introduction, high performing NLP's neural models often require huge volumes of annotated data to produce powerful models and prevent over-fitting.
in the case of social media content, it is difficult to achieve the performances of state-of-the-art models based on hand-crafted features by applying neural models trained on small amounts of annotated data.