@inproceedings{khanna-etal-2022-idiap,
    title = "{IDIAP}{\_}{TIET}@{LT}-{EDI}-{ACL}2022 : Hope Speech Detection in Social Media using Contextualized {BERT} with Attention Mechanism",
    author = "Khanna, Deepanshu  and
      Singh, Muskaan  and
      Motlicek, Petr",
    editor = "Chakravarthi, Bharathi Raja  and
      Bharathi, B  and
      McCrae, John P  and
      Zarrouk, Manel  and
      Bali, Kalika  and
      Buitelaar, Paul",
    booktitle = "Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.ltedi-1.49/",
    doi = "10.18653/v1/2022.ltedi-1.49",
    pages = "321--325",
    abstract = "With the increase of users on social media platforms, manipulating or provoking masses of people has become a piece of cake. This spread of hatred among people, which has become a loophole for freedom of speech, must be minimized. Hence, it is essential to have a system that automatically classifies the hatred content, especially on social media, to take it down. This paper presents a simple modular pipeline classifier with BERT embeddings and attention mechanism to classify hope speech content in the Hope Speech Detection shared task for Equality, Diversity, and Inclusion-ACL 2022. Our system submission ranks fourth with an F1-score of 0.84. We release our code-base here \url{https://github.com/Deepanshu-beep/hope-speech-attention} ."
}