Emotional Context Detection on Conversation Text with Deep Learning Method Using Long Short-Term Memory and Attention Networks
Afrida Helen, Mira Suryani, Hidayatul Fakhri · 2021
The conversation in the text is an interesting research on Natural Language Processing. One of the text conversation tasks is to know the emotions of the people involved in the conversation. The conversation in social media like Twitter, Instagram, short message service, WhatsApp, and so on, often involves emotion. Somehow the comments are impulsive sentences that can stimulate emotions. Expressing emotions using text are rarely done and uncomfortable. However, with natural language technology development, expressing emotions using text can be succeeded with specific symbols. We call the specific symbols emojis. So many emojis can express emotions. This research proposes the emoji symbol as a character feature. We introduce the Emoji2Vec method and Long Short-term Memory with Attention. The Attention that is used has a complex topology. We compared the results of this study with the baseline model. The method we propose is better than the baseline model.