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

May 15, 2022 ... This tool was used to collect and analyze tweets at scale in real time to study sentiment and key terms of interest. Separate tweet analysis ... 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 ... VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed ... Evaluating customer sentiment. It can be used to find both an organization's happy and unhappy customers, giving insight into what's working for your business ... 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 ... We present a new method for sentiment classification based on extracting and analyzing appraisal groups such as ``very good'' or ``not terribly funny''. An ... Sep 11, 2023 ... Opinionated pieces of text can be further divided into negative and positive, using polarity classification. This technique works for large- ... Mar 14, 2025 ... SVM is a popular machine learning algorithm used in sentiment analysis models. It classifies text data by finding the optimal hyperplane that ... Oct 25, 2022 ... Sentiment analysis classifies the sentiment of the reviews into positive or negative sentiment. You use the Sentiment workflow to train a BERT- ... Sentiment analysis can also be used to track customer sentiment over time, helping decision-makers identify positive or negative long-term trends.