Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/108776
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Type: Conference paper
Title: Sentiment analysis over social networks: an overview
Author: Ahmed, K.
Tazi, N.
Hossny, A.
Citation: Conference proceedings / IEEE International Conference on Systems, Man, and Cybernetics. IEEE International Conference on Systems, Man, and Cybernetics, 2015, pp.2174-2179
Publisher: IEEE
Issue Date: 2015
Series/Report no.: IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
ISBN: 9781479986965
ISSN: 1062-922X
Conference Name: 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2015) (9 Oct 2015 - 12 Oct 2015 : Hong Kong)
Statement of
Responsibility: 
Khaled Ahmed, Neamat El Tazi, Ahmad Hany Hossny
Abstract: The rapid increase in data on social media creates a need for mining such data to get valuable insights. The data type can be unstructured with large volumes. Sentiment analysis addresses such need by detecting opinions or emotions on the social media text. Sentiment analysis can be performed in various domains such as social, medical and industrial applications. This paper presents a survey about sentiment analysis addressing the different concepts in this area, problems and its solutions, available APIs, tools used and presenting a list of open challenges in this area.
Keywords: Sentiment lexicons and emotion detection; social media; sentiment analysis; feature selection; recommendation; spam detection
Rights: © 2015 IEEE
DOI: 10.1109/SMC.2015.380
Published version: http://dx.doi.org/10.1109/smc.2015.380
Appears in Collections:Aurora harvest 3
Mathematical Sciences publications

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