What are some domain-specific challenges in sentiment analysis (e.g., medical, legal)?

Apr 7, 2022 ... This study performs both sentiment analysis and emotion detection using the tweets related to the cryptocurrency which are widely used for predicting the ... Broadly speaking, sentiment analysis is most effective when used as a tool for Voice of Customer and Voice of Employee. Business analysts, product managers, ... Oct 25, 2022 ... Sentiment analysis classifies the sentiment of the reviews into positive or negative sentiment. You use the Sentiment workflow to train a BERT- ... Companies can also use sentiment analysis of previous products as a measure for launching new products, advertising campaigns, or breaking news about your ... Mar 30, 2024 ... It's a form of data science that uses AI, machine learning, and natural language processing (NLP) to uncover human feelings within a message or ... We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with ... Evaluating customer sentiment. It can be used to find both an organization's happy and unhappy customers, giving insight into what's working for your business ... Apr 8, 2024 ... One example is market sentiment monitoring, which uses sentiment analysis to monitor overall sentiment and public opinion on industry trends, ... Mar 7, 2023 ... In this blog, we'll demonstrate how to perform sentiment analysis with the space features in BigQuery ML by training and inferencing machine learning models ... Feb 21, 2025 ... An overview of the sentiment analysis feature in Azure AI services, which helps you find out what people think of a topic by mining text for ...