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We use the BERT language model for Twitter sentiment analysis leading to the US 2020 presidential elections. We investigate if sentiment analysis can provide an indication of the outcome of the results using canonical LSTM and BERT language model.
Audio Analyser, a cutting-edge application designed to transform audio recordings into actionable insights using Microsoft Azure AI. It offers audio recording, speech-to-text conversion, and in-depth text analysis, providing users with comprehensive and insightful reports.
Sentiment analysis categorizes the emotional tone of text, using natural language processing and machine learning. It helps businesses gain insights from customer feedback, social media, and more, to understand public opinion, make data-driven decisions, and manage brand reputation.
Conduct sentiment analysis and identify what makes a product so good or bad by identifying its keywords. Analyses involved : sentiments, text cleansing, regex, word count