LUCID: lexicon-augmented fusion with ordinal calibration for multimodal sentiment analysis

Key Points

• The study demonstrates improved sentiment prediction accuracy through lexicon-augmented fusion techniques and ordinal calibration.
• Results show a notable increase in sentiment analysis performance, outperforming traditional methods.
• Analysis involved applying cutting-edge machine learning techniques to various data modalities, revealing significant advancements.
• Findings support the potential for more accurate sentiment analysis in real-world applications, particularly in user-generated content.