Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect

Citation

Hussien IO, Dashtipour K & Hussain A (2018) Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect. In: Ren J, Hussain A, Zheng J, Liu C, Luo B, Zhao H & Zhao X (eds.) Advances in Brain Inspired Cognitive Systems. BICS 2018. Lecture Notes in Computer Science, 10989. BICS 2018: International Conference on Brain Inspired Cognitive Systems, Xi'an, China, 07.07.2018-08.07.2018. Cham, Switzerland: Springer Verlag, pp. 615-624. https://doi.org/10.1007/978-3-030-00563-4_60

Abstract
Sentiment analysis mainly focused on the automatic recognition of opinions’ polarity, as positive or negative. Nowadays, sentiment analysis is replacing the web-based and traditional survey methods commonly conducted by companies for finding the public opinion about their products and services to improve their marketing strategy and product advertisement and help to improve customer service. The online availability of large text makes it important to be analyzed. The automatic analysis of this information involves a deep understanding of natural languages. Sentiments and emotions play a pivotal role in our daily lives. They assist decision-making, learning, communication, and situation awareness in human environments. The importance of processing and understanding dialect text is increasing due to the growth of socially generated dialectal content in social media. In addition to existing materials such as local proverbs, advice and folklore that are found spread on the web. This paper focused on text sentiment analysis as dialect text, as quick review to identify relevant contributions that address languages aspect for a specific dialect.

Keywords
Sentiment analysis; Affecting analysis; Arabic text; Dialect