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Contextual Emotion Classification in Text Using Hybrid Word2Vec-BiLSTM

by Nilla Sivasrinu , Suneel Kumar Duvvuri
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Current price ₹7,345.00
Original price ₹7,540.00
Original price ₹7,540.00
Original price ₹7,540.00
(-3%)
₹7,345.00
Current price ₹7,345.00

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Book cover type: Paperback
  • ISBN13: 9786209879531
  • Binding: Paperback
  • Subject: N/A
  • Publisher: LAP Lambert Academic Publishing
  • Publisher Imprint: LAP Lambert Academic Publishing
  • Publication Date:
  • Pages: 116
  • Original Price: GBP 58.0
  • Language: English
  • Edition: N/A
  • Item Weight: 164 grams
  • BISAC Subject(s): General

In the modern digital era, human communication has shifted significantly toward unstructured text found on social media, micro-blogs, and instant messaging platforms. While traditional face-to-face interactions rely on non-verbal cues like facial expressions and vocal tone, digital text lacks these signals, making the detection of emotional intent a complex challenge for Natural Language Processing (NLP). This study addresses the limitations of traditional machine learning methods, such as Na�ve Bayes and Logistic Regression, which often fail to capture contextual meaning and long-range sequential dependencies. The proposed research introduces a hybrid deep learning framework that integrates Word2Vec(Continuous Bag-of-Words) embeddings with a Bidirectional Long Short-Term Memory (BiLSTM) network. Word2Vec is utilized to extract dense semantic features, enabling the model to understand mathematical relationships between words.

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