What is accuracy in the context of sentiment analysis evaluation?

The sentiment analysis packages we will be used to obtain our sentiment scores are free-to-use and brought to you by the wonderful R community. Sentiment Analysis predicts sentiment for each document in a corpus. It uses Liu & Hu and Vader sentiment modules from NLTK, multilingual sentiment lexicons. Jun 16, 2015 ... In this paper, we aim to tackle the problem of sentiment polarity categorization, which is one of the fundamental problems of sentiment analysis. 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 ... Broadly speaking, sentiment analysis is most effective when used as a tool for Voice of Customer and Voice of Employee. Business analysts, product managers, ... Sentiment analysis uses natural language processing (NLP) and machine learning (ML) technologies to train computer software to analyze and interpret text in a ... Jul 1, 2019 ... For this purpose, authors have used Twitter to detect and classify terrorist events by utilizing civilian sentiments. ... using sentiment analysis ... Apr 23, 2018 ... This study suggests that there is a need for an accurate and tested tool for sentiment analysis of tweets trained using a health care setting–specific corpus. Nov 8, 2024 ... Yes, an AI system for sentiment analysis can be an AI system to infer emotions of a natural person in the workplace or educational institutions. Apr 15, 2022 ... Traditionally sentiment analysis is used to consider customer feedback, employee engagement, survey responses, and product reviews. Monitoring ...