A Practical Guide to Sentiment Analysis

By Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, Antonio Feraco. 2017

400 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ce42f2d7595e995993ce9f6b603a1fb2111b2006

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In Artificial Intelligence

Citations in the corpus

A survey on sentiment analysis methods, applications, and challenges (2022, background): “Affective computing and sentiment analysis also have tremendous potential as a subsystem technology for other systems (Cambria et al. 2017).”
Context-Dependent Sentiment Analysis in User-Generated Videos (2017, background): “Text-based sentiment analysis systems can be broadly categorized into knowledge-based and statistics-based approaches (Cambria et al., 2017a).”
Sentiment Analysis Based on Deep Learning: A Comparative Study (2020, background): “analysis continue to face theoretical and technical issues that hinder their overall accuracy in polarity detection [3,4].”
Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM (2018, background): “In recent years, sentiment analysis (Cambria et al. 2017a) has become increasingly popular for processing social media data on online communities, blogs, wikis, microblogging platforms, and other online collaborative media.”
Spoken Conversational AI in Video Games: Emotional Dialogue Management Increases User Engagement (2018, background): “This can be done using a variety of platforms such as online view platforms and social media websites [1].”
Tensor Fusion Network for Multimodal Sentiment Analysis (2017, background): “This generalization is particularly vital to part of the NLP community dealing with opinion mining and sentiment analysis (Cambria et al., 2017) since there is a growing trend of sharing opinions in videos instead of text, specially in social media (Facebook, YouTube, etc.”
Bayesian network based extreme learning machine for subjectivity detection (2017, background): “In recent years, sentiment analysis of social media data on blogs, online communities, Wikis, microblogging platforms, and other online collaborative media has become increasingly popular [1].”