A survey of sentiment analysis in social media

By Lin Yue, Weitong Chen, Xue Li, Wanli Zuo, Minghao Yin. Knowledge and Information Systems, 2018

563 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances (2022, unknown): “[47] 2019               ”
Sentiment Analysis in the Era of Large Language Models: A Reality Check (2023, background): “…human subjective sentiments and opinions toward achieving human-level intelligence (Bubeck et al., 2023), and its broad practical applications, such as analyzing customer reviews (Keung et al., 2020; Zhang et al., 2022) and digesting social media opinions (Yue et al., 2019; Barbieri et al., 2020).”
Transformer models for text-based emotion detection: a review of BERT-based approaches (2021, background): “NLP’s favored applications, such as translation systems, search engines, natural language assistants, sentiment, and opinion analysis, are resolving societal issues at an unprecedented rate (Yue et al. 2019; Gobinda 2003; Wang et al. 2019).”
A survey on sentiment analysis methods, applications, and challenges (2022, background): “Additionally, In the work of Yue et al. (2019) and Liu et al. (2012) conducted research on the effectiveness of internet reviews.”
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications (2019, background): “Detection on social content focuses on feature engineering [11], [12], sentiment analysis [13], [14], and deep learning [15], [16], [17].”