A survey on sentiment classification algorithms, challenges and applications

• Main Authors: Rana Muhammad Rizwan Rashid, Nawaz Asif, Iqbal Javed
• Format: Article
• Language: English
• Published: Sciendo 2018-08-01
• Series: Acta Universitatis Sapientiae: Informatica
• Subjects: sentiment classification; supervised learning; opinion mining; machine learning; lexicon approaches; unsupervised learning; 68r15
• Online Access: https://doi.org/10.2478/ausi-2018-0004

Sentiment classification is the process of exploring sentiments, emotions, ideas and thoughts in the sentences which are expressed by the people. Sentiment classification allows us to judge the sentiments and feelings of the peoples by analyzing their reviews, social media comments etc. about all the aspects. Machine learning techniques and Lexicon based techniques are being mostly used in sentiment classification to predict sentiments from customers reviews and comments. Machine learning techniques includes several learning algorithms to judge the sentiments i.e Navie bayes, support vector machines etc whereas Lexicon Based techniques includes SentiWordnet, Wordnet etc. The main target of this survey is to give nearly full image of sentiment classification techniques. Survey paper provides the comprehensive overview of recent and past research on sentiment classification and provides excellent research queries and approaches for future aspects