What are the challenges of performing sentiment analysis on text with economic terms?

... 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 ... Jul 21, 2024 ... I'm looking to perform sentiment analysis using local Ollama models and would like your recommendations. Specifically, I'm interested in knowing which models ... We present a new method for sentiment classification based on extracting and analyzing appraisal groups such as ``very good'' or ``not terribly funny''. An ... We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with ... Feb 2, 2022 ... Sentiment analysis is a natural language processing technique that identifies the polarity of a given text. There are different flavors of ... Sep 28, 2024 ... How does Sentiment Analysis work? · Document-level – for the entire text. · Sentence-level – obtains the sentiment of a single sentence. · Sub- ... 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 ... Sentiment analysis can also be used to track customer sentiment over time, helping decision-makers identify positive or negative long-term trends. Sep 15, 2011 ... Hauffa, 2011), sentiment analysis was used to characterize social relations. ... opinion-related features, which showed that 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 ...