What are the challenges of performing sentiment analysis on text with domain-specific jargon?

This guide is designed to help you learn how to bring artificial intelligence (AI) to open data lakehouses with Snowflake Cortex AI and Iceberg Tables. Apr 23, 2018 ... Multiple methods are used for sentiment analysis of tweets in the health care setting. These range from self-produced basic categorizations ... Meanwhile, the negative review results are used as recommendations for future improvements in tourist attractions. Keywords: text mining, sentiment analysis, ... VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed ... Feb 21, 2022 ... Sentiment analysis is a way of using computers to evaluate the emotion or connotation of words within texts. Jun 13, 2024 ... In this study, we address the gaps by developing a deep learning-based approach for sentiment analysis. We have collected 24,360 comments from ... Sep 9, 2021 ... Sentiment analysis defined. Sentiment analysis is analytical technique that uses statistics, natural language processing, and machine learning ... Sep 18, 2024 ... While both are used to detect emotions, they analyze different types of data and employ different technologies. Sentiment analysis uses text and ... Aug 8, 2022 ... Sentiment analysis predominantly uses NLP and ML to make sense of the linguistic nuances observed in user interactions. The foundations of ... Sentiment analysis uses natural language processing (NLP) and machine learning (ML) technologies to train computer software to analyze and interpret text in a ...