ARAACOM: ARAbic Algerian Corpus for Opinion Mining
This work addresses a gap in opinion mining for Arabic Algerian, but it is incremental as it focuses on dataset creation without novel methodological advancements.
The authors tackled the scarcity of resources for opinion mining in Arabic Algerian by creating ARAACOM, a corpus for sentiment analysis, though no specific performance metrics or results are provided.
Nowadays, it is no more needed to do an enormous effort to distribute a lot of forms to thousands of people and collect them, then convert this from into electronic format to track people opinion about some subjects. A lot of web sites can today reach a large spectrum with less effort. The majority of web sites suggest to their visitors to leave backups about their feeling of the site or events. So, this makes for us a lot of data which need powerful mean to exploit. Opinion mining in the web becomes more and more an attracting task, due the increasing need for individuals and societies to track the mood of people against several subjects of daily life (sports, politics, television,...). A lot of works in opinion mining was developed in western languages especially English, such works in Arabic language still very scarce. In this paper, we propose our approach, for opinion mining in Arabic Algerian news paper. CCS CONCEPTS $\bullet$Information systems~Sentiment analysis $\bullet$ Computing methodologies~Natural language processing