Name
Abstract | ||
|---|---|---|
AbstractSentiment Analysis/Opinion Mining is associated with social media and usually aims to automatically identify the polarities of different points of views of the users of the social media about different aspects of life. The polarity of a sentiment reflects the point view of its author about a certain issue. This study aims to present a new method to identify the polarity of Arabic reviews and comments whether they are written in Modern Standard Arabic MSA, or one of the Arabic Dialects, and/or include Emoticons. The proposed method is called Detection of Arabic Sentiment Analysis Polarity DASAP. A modest dataset of Arabic comments, posts, and reviews is collected from Online social network websites i.e. Facebook, Blogs, YouTube, and Twitter. This dataset is used to evaluate the effectiveness of the proposed method DASAP. Receiver Operating Characteristic ROC prediction quality measurements are used to evaluate the effectiveness of DASAP based on the collected dataset. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.4018/IJITWE.2016070103 | Periodicals |
Keywords | Field | DocType |
Arabic Multi-Media Classification, Arabic Text Analysis, Arabic Text Classification, Big Data, Document-Level, Opinion Mining, Sentiment Analysis, Social Network | Data mining,Social network,Social media,Arabic,Computer science,Sentiment analysis,Modern Standard Arabic,Natural language processing,Artificial intelligence,Big data | Journal |
Volume | Issue | ISSN |
11 | 3 | 1554-1045 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammed N. Al-Kabi | 1 | 52 | 5.74 |
| Heider Wahsheh | 2 | 0 | 0.34 |
| Izzat Alsmadi | 3 | 229 | 44.37 |