Survey on mining subjective data on the web

By Mikalai Tsytsarau, Themis Palpanas. Data mining and knowledge discovery, 2011

483 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/e98ab6eb7fad7b9e8c4473fb92e4fe61cc450659

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Citations in the corpus

Sentiment analysis algorithms and applications: A survey (2014, background): “Although [1] mentioned the problems of opinion aggregation and contradiction analysis, they were not found in the recent articles presented by this survey.”
Sentiment analysis: A review and comparative analysis of web services (2015, background): “And on the other hand, Tsytsarau and Palpanas mainly focus on opinion aggregation, opinion spam and contradictions analysis, especially applied to Web services, for example, microblogs or streaming data, among others [88].”
A survey of sentiment analysis in social media (2018, background): “[125] reviewed the development of sentiment analysis in recent years and also discussed the gradual progress of a research direction, namely contradiction analysis.”
UTiLearn: A Personalised Ubiquitous Teaching and Learning System for Smart Societies (2017, background): “Current issues, trends and future prospects of SA are discussed comprehensively in surveys [44], [45].”
Document-level sentiment classification: An empirical comparison between SVM and ANN (2013, methodology): “…in terms of the adopted approach for feature selection, since most of them agree ll rights reserved. oraes), jfvaliati@unisinos.br on the learning techniques: Support Vector Machine (SVM) and Naı̈ve Bayes (NB) (Abbasi, Chen, & Salem, 2008; Tang, Tan, & Cheng, 2009; Tsytsarau & Palpanas, 2012).”
Survey on Aspect-Level Sentiment Analysis (2016, background): “Tsytsarau and Palpanas [7] published a survey in 2011 that, while still focusing on document-level sentiment analysis, distinguishes between four different approaches for identifying the sentiment value of words: machine”
Like It or Not (2016, background): “According to Tsytsarau and Palpanas [2012], OM is about determining whether a piece of text contains opinion, a problem that is also known as subjectivity analysis , whereas the focus of SA is the sentiment polarity detection by which the opinion of the examined text is assigned a positive or…”
Sentiment Analysis in Tourism: Capitalizing on Big Data (2019, methodology): “The dictionary-based approach also includes a subcategory called semantic-based approach (Tsytsarau & Palpanas, 2012).”
A survey on opinion mining and sentiment analysis: Tasks, approaches and applications (2015, background): “Tsytsarau and Palpanas [137] presented a survey on SA by focusing on opinion mining, opinion aggregation including spam detection and contradiction”