A survey on opinion mining and sentiment analysis: Tasks, approaches and applications

By Kumar Ravi, Vadlamani Ravi. 2015

1,235 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

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Citations in the corpus

A review on sentiment analysis from social media platforms (2023, background): “This reality continues to be true even after hundreds of articles and extensive review papers Ravi & Ravi (2015); Ashima & Kumar (2020) have been published.”
A survey of sentiment analysis in social media (2018, background): “[106] is organized on the basis of sub-tasks to be performed, that is to say, machine learning, natural language processing techniques, and applications of sentiment analysis.”
Sentiment analysis using deep learning architectures: a review (2019, background): “The sentiment analysis tasks can be categorized into two parts (Ravi and Ravi 2015): core (or major) tasks which are referred as the basic sentiment analysis tasks, and second category includes the sub-tasks that are called sub-categories of the major tasks.”
The evolution of sentiment analysis - A review of research topics, venues, and top cited papers (2016, background): “In 2015, Ravi and Ravi [Ravi and Ravi 2015] gave a broad introduction to the field of sentiment analysis.”
A survey of the applications of text mining in financial domain (2016, background): “Recently, a survey on the works published during 2002-2014 on sentiment analysis and opinion mining was conducted by Ravi and Ravi (2015).”
A survey on classification techniques for opinion mining and sentiment analysis (2017, background): “Several recent surveys and reviews on sentiment analysis consider these levels of opinion mining from this point of view (Medhat et al. 2014; Ravi and Ravi 2015; Balazs and Velasquez 2016; Yan et al. 2017; Sun et al. 2017; Lo et al. 2017).”
A survey on sentiment analysis methods, applications, and challenges (2022, background): “According to Medhat et al. (2014), Ravi and Ravi (2015) ANN had the edge over SVM in most of the cases, except very few cases where there was a data imbalance.”
Big data techniques in auditing research and practice: Current trends and future opportunities (2018, neutral): “Ravi and Ravi (2015) review a study that analysed Enron emails (Mohammad, 2012) to reveal marked differences by gender in the use of emotional words, particularly those about trust.”