Preprocessing Arabic Dialect for Sentiment Mining: State of Arte

EasyChair Preprint no. 4069

Abstract

Sentiment Analysis, concerns with the analysis of ideas, emotions, evaluations, values, attitudes and feelings about products, services, companies, individuals, tasks, events, titles and their characteristics. With the increase in applications on the Internet and social networks, Sentiment Analysis has become more crucial in the field of text mining research and has since been used to explore the opinions of users about various products or topics discussed over the Internet. Developments in the fields of Natural Language Processing and Computational Linguistics have contributed positively to Sentiment Analysis studies especially for sentiments written in non-structured or semi-structured languages.  In this paper, we presents a literature review on the preprocessing, an analytical and comparative study of different researches conducted on sentiment analysis in Arabic social networks. Our comparison analyzes in more detail the preprocessing (stop words, stemming…) steps which are very important in sentiment analysis process success and are the most difficult especially in the case where the comments are written in Arabic dialect.

Keyphrases: Arabic Dialect, Preprocessing, Sentiment Mining, Stemming, Stop words

@Booklet{EasyChair:4069,
  author = {Zineb Nassr and Nawal Sael and Faouzia Benabbou},
  title = {Preprocessing Arabic Dialect for Sentiment Mining: State of Arte},
  howpublished = {EasyChair Preprint no. 4069},

  year = {EasyChair, 2020}}