Sentiment analysis algorithms and applications: A survey

• Published in: Ain Shams Engineering Journal Vol. 5; no. 4; pp. 1093 - 1113
• Main Authors: Medhat, Walaa, Hassan, Ahmed, Korashy, Hoda
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2014; Elsevier
• Subjects: Building resources; Emotion detection; Feature selection; Sentiment analysis; Sentiment classification; Transfer learning; Sentiment analysis; Feature selection; Emotion detection; Transfer learning; Building resources; Sentiment classification
• ISSN: 2090-4479
• DOI: 10.1016/j.asej.2014.04.011

Sentiment Analysis (SA) is an ongoing field of research in text mining field. SA is the computational treatment of opinions, sentiments and subjectivity of text. This survey paper tackles a comprehensive overview of the last update in this field. Many recently proposed algorithms' enhancements and various SA applications are investigated and presented briefly in this survey. These articles are categorized according to their contributions in the various SA techniques. The related fields to SA (transfer learning, emotion detection, and building resources) that attracted researchers recently are discussed. The main target of this survey is to give nearly full image of SA techniques and the related fields with brief details. The main contributions of this paper include the sophisticated categorizations of a large number of recent articles and the illustration of the recent trend of research in the sentiment analysis and its related areas.