What are the challenges of performing sentiment analysis on text with implied meaning?

Nov 27, 2023 ... Conventional sentiment analysis methods often fail to capture this heterogeneity, potentially leading to misjudged economic consequences for ... Broadly speaking, sentiment analysis is most effective when used as a tool for Voice of Customer and Voice of Employee. Business analysts, product managers, ... 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 ... Using sentiment algorithms, developers and brand managers can gain insights into customer opinions about a topic. Why is sentiment important to measure? Sentiment analysis is an NLP technique used to determine and extract the sentiments and opinions expressed in the text data. Jun 18, 2018 ... There has been substantial work on sentiment classification on reviews and comments from interactive websites using machine learning techniques ... Specifically, the self-attention mechanism enables AMIC to generate context-aware word embeddings, assigning document-specific sentiment scores to words based ... Sep 15, 2018 ... The traditional approaches to Twitter Sentiment Analysis (TSA) include dictionary-based and use supervised machine learning tools for sentiment ... Apr 15, 2022 ... Traditionally sentiment analysis is used to consider customer feedback, employee engagement, survey responses, and product reviews. Monitoring ... 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 ...