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

Sentiment analysis, also known as opinion mining, is the process that uses natural language processing (NLP) and machine learning (ML) techniques to analyze the ... Sep 15, 2011 ... Hauffa, 2011), sentiment analysis was used to characterize social relations. ... opinion-related features, which showed that sentiment analysis ... Mar 11, 2025 ... AI-driven sentiment analysis can assess whether a brand's messaging aligns with customer perceptions. This alignment check empowers companies to ... 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 ... The 8 Top Sentiment Analysis Python Packages & Libraries · #1 NLTK. NLTK (Natural Language Toolkit) is a Python library for natural language processing that ... 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 also be used to track customer sentiment over time, helping decision-makers identify positive or negative long-term trends. Learn what sentiment analysis is, why it's important to your brand and ... used in customer feedback. Sentiment analysis tools look for particular ... 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 ... Apr 23, 2018 ... Multiple methods are used for sentiment analysis of tweets in the health care setting. These range from self-produced basic categorizations ...