Financial sentiments Analysis-FinBERT Workflow: This workflow uses finbert, A BERT-based model fine-tuned on financial text for high-accuracy sentiment analysis in the finance domain. Sentimental Analysis using LLMs Large Language Models (LLMs), like GPT (Generative Pretrained Transformer) variants, ...
This perspective paper is written to capture and analyze the various mental state health issues being perceived via emotional analysis of Twitter data during the COVID-19 virus outbreak from a single nation further spread of to the whole world. A data-driven approach with higher accuracy as here...
Sentimental analysis on these genuine Twitter accounts is performed by modifying the Natural Language Processing (NLP) state-of-art algorithm called Bidirectional Encoder Representations from Transformers (BERT). The proposed method achieved 88.30% of classification accuracy rate by concatenation of the ...
Then, we designed the word clouds and classified the sentiments using the BERT model. We then performed the geo-coding and visualized the feature points over the world map. We found the correlation between the feature points geographically and then applied hotspot analysis and kernel density ...
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