Papers with sentiment analysis model

3 papers
Multi-source Multi-domain Sentiment Analysis with BERT-based Models (2022.lrec-1)

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Challenge: Sentiment analysis is a widely studied task in natural language processing.
Approach: They propose to improve BERT-based models for sentiment analysis on italian corpora and evaluate their performance on the basis of eight corpors.
Outcome: The proposed model is evaluated over eight sentiment analysis corpora from different domains and sources on the prediction of positive, negative and neutral classes.
A Text-Centered Shared-Private Framework via Cross-Modal Prediction for Multimodal Sentiment Analysis (2021.findings-acl)

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Challenge: Existing studies treat all three modal features equally and implicitly explore the interactions between different modalities.
Approach: They propose a text-centered shared-private framework for multimodal fusion . they propose modalities that can provide shared and private semantics .
Outcome: The proposed framework outperforms baselines on the MOSEI and MOSI datasets.
Learning Explicit and Implicit Structures for Targeted Sentiment Analysis (D19-1)

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Challenge: Existing research efforts focus on targeting sentiment analysis as a sequence labeling problem, building models that can capture explicit structures in the output space.
Approach: They argue that both implicit and explicit structural information are crucial for building a successful targeted sentiment analysis model.
Outcome: The proposed model outperforms existing models by capturing implicit and explicit structural information.

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