What are the challenges of performing sentiment analysis on text with historical figures' names?

We present a new method for sentiment classification based on extracting and analyzing appraisal groups such as ``very good'' or ``not terribly funny''. An ... Jun 16, 2018 ... We present a novel feature fusion strategy that proceeds in a hierarchical fashion, first fusing the modalities two in two and only then fusing all three ... Dec 5, 2022 ... Sentiment analysis of vegan related tweets using mutual information for feature selection. Elvina Shamoi 1 , Akniyet Turdybay 1 , Pakizar Shamoi 1 , Iskander ... Dec 17, 2023 ... Sentiment analysis, also known as opinion mining, is a technique used in natural language processing (NLP) to identify and extract sentiments or ... Sentiment analysis is the process of analyzing digital text to determine if the emotional tone of the message is positive, negative, or neutral. Using sentiment algorithms, developers and brand managers can gain insights into customer opinions about a topic. Why is sentiment important to measure? Jul 1, 2019 ... For this purpose, authors have used Twitter to detect and classify terrorist events by utilizing civilian sentiments. ... using sentiment analysis ... Feb 5, 2025 ... Learn the what, why and how of social media sentiment analysis: its importance, challenges, how to use sentiment insights for your business ... Nov 27, 2023 ... Conventional sentiment analysis methods often fail to capture this heterogeneity, potentially leading to misjudged economic consequences for ... 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 ...