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

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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 ... 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 is used in business intelligence to understand the subjective reasons why consumers are or are not responding to something (e.x. why are ... 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 ... 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 ... ... 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 ... Sep 15, 2011 ... Hauffa, 2011), sentiment analysis was used to characterize social relations. ... opinion-related features, which showed that sentiment analysis ... VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed ... 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 ... Jun 13, 2024 ... In this study, we address the gaps by developing a deep learning-based approach for sentiment analysis. We have collected 24,360 comments from ...
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