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

We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with ... Sep 9, 2021 ... Sentiment analysis defined. Sentiment analysis is analytical technique that uses statistics, natural language processing, and machine learning ... A sentiment analysis tool can also be used for monitoring. As an extension of brand perception monitoring, sentiment analysis can be an invaluable crisis ... Mar 19, 2021 ... In this work, the sentiment analysis is performed with the help of the BERT model on the twitter data sets. The data set is categorized on the ... Furthermore, we align these word embeddings and present a novel neural network model that is trained on English data to conduct sentiment analysis and then ... Mar 11, 2025 ... AI-driven sentiment analysis can assess whether a brand's messaging aligns with customer perceptions. This alignment check empowers companies to ... 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 ... Sep 28, 2024 ... How does Sentiment Analysis work? · Document-level – for the entire text. · Sentence-level – obtains the sentiment of a single sentence. · Sub- ... Oct 9, 2020 ... I'll start by defining the first unusual term in the title: Sentiment Analysis is a very frequent term within text classification and is ... Sentiment analysis uses natural language processing (NLP) and machine learning (ML) technologies to train computer software to analyze and interpret text in a ...