What are the challenges of performing sentiment analysis on text with similes?

Jul 22, 2024 ... Applying LLMs to sentiment analysis. Sentiment analysis is a use case that is deeply affected by LLMs due to their ability to understand context ... 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 ... A Sentimental Education: Sentiment Analysis Using Subjectivity. Summarization Based on Minimum Cuts. Bo Pang and Lillian Lee. Department of Computer Science. Sentiment analysis can tell you which customers feel negatively about your brand for whatever reason. For example, you could find out that negative sentiment is ... Jun 18, 2018 ... There has been substantial work on sentiment classification on reviews and comments from interactive websites using machine learning techniques ... Sep 28, 2024 ... How does Sentiment Analysis work? · Document-level – for the entire text. · Sentence-level – obtains the sentiment of a single sentence. · Sub- ... Using sentiment algorithms, developers and brand managers can gain insights into customer opinions about a topic. Why is sentiment important to measure? 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 ... Sep 9, 2021 ... Sentiment analysis defined. Sentiment analysis is analytical technique that uses statistics, natural language processing, and machine learning ... Feb 2, 2024 ... This is often used to understand the attitudes, opinions, and emotions expressed in an online mention, a review, or a piece of text. The primary ...