Aspect based Sentiment & Emotion Analysis with ROBERTa, LSTM

Internet usage has increased social media over the past few years, significantly impacting public opinion on online networks. Nowadays, these websites are considered most appropriate place to express feelings and opinions. The popular site Twitter offers valuable insight into people’s thoughts. Throughout conflict between Russia Ukraine, people from all world have expressed their In this study, ”machine–learning” & ”deep–learning” techniques used understand emotions views about war revealed. This study unveils a novel deep-learning approach that merges best features of sequence transformer models while fixing respective flaws. model combines Roberta with ABSA(Aspect based sentiment analysis) Long Short-Term Memory for analysis. A large dataset geographically tagged tweets related Ukraine-Russia was collected Twitter. We analyzed using Roberta-based model. contrast, can effectively capture long-distance contextual semantics. Robustly optimized BERT ABSA maps words compact, meaningful word embedding space. accuracy suggested hybrid is 94.7%, which higher than state-of-the-art techniques.