Abstract
This paper presents proposed performance criteria evaluation based on a comparison between sentiment techniques. The target is measuring the sentiments performance through several significant perspectives in sentiment analysis. This measurement is very tight of accuracy evaluating for sentiments. However, evaluating sentiments is a hard challenge for language technologies, and achieving good results is much more difficult than some human think. Also, we introduce a comprehensive study for different sentiment techniques based on proposed performance criteria. The performance evaluation plays a vital role in accuracy measurement through a sentiment analysis word level. The performance criteria include two types of performance measurement namely F-measure and Runtime. These criteria include the balance of performance perspectives priorities. These types include a relationship between perspectives of performance to improve it. There are different performance perspectives: F-measure and speed of run time, memorability, and sentiment analysis challenges. It helps in understanding the contextual meaning and getting a score in less time and higher accuracy. The comparisons are based on the sentiment analysis word-level. They can understand some phrases as do not directly through caring with the classification of reviews. Finally, we show the efficiency and effectiveness of the proposed criteria.
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Mohamed, D.M.ED., El-din, M.H.N. (2018). Performance Analysis for Sentiment Techniques Evaluation Perspectives. In: Hassanien, A., Shaalan, K., Gaber, T., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017. AISI 2017. Advances in Intelligent Systems and Computing, vol 639. Springer, Cham. https://doi.org/10.1007/978-3-319-64861-3_42
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