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

Jul 7, 2016 ... Sentiment analysis can also provide analytical perspectives for financial investors who want to discover and respond to market opinions [3, 4]. Sentiment analysis provides an effective way to evaluate written or spoken language to determine if the expression is favorable, unfavorable, or neutral. Sentiment Analysis predicts sentiment for each document in a corpus. It uses Liu & Hu and Vader sentiment modules from NLTK, multilingual sentiment lexicons. 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 ... Sep 11, 2023 ... Opinionated pieces of text can be further divided into negative and positive, using polarity classification. This technique works for large- ... 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 ... ... used for fine-tuning the LLM (Step 4). State-of-the-art pre-trained LLMs can perform sentiment analysis without any fine-tuning using zero-shot or few-shot ... The 8 Top Sentiment Analysis Python Packages & Libraries · #1 NLTK. NLTK (Natural Language Toolkit) is a Python library for natural language processing that ... Feb 26, 2018 ... In essence, it is the process of determining the emotional tone behind a series of words, used to gain an understanding of the the attitudes, ... Sep 28, 2024 ... How does Sentiment Analysis work? · Document-level – for the entire text. · Sentence-level – obtains the sentiment of a single sentence. · Sub- ...