Abstract: The classification of emotional states in poetry or formal texts has received less attention from experts in computational intelligence than informal textual content, such as SMS, email, chat, and online user reviews.
This work introduces a technique for classifying emotional states in poetry using cutting-edge Artificial Intelligence technology known as Deep Learning in order to fill this knowledge gap. To analyse the poetry corpus and categorise the text into different emotional states, such as love, joy, hope, grief, anger, and others, the system uses an attention-based C-LSTM model.
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DOI:
10.17148/IJARCCE.2023.125238
