Recently, Opinion Mining (OM) is receiving more attention due to the abundance of forums, blogs, ecommerce web sites, news reports and additional web sources where people tend to express their opinions. There are a number of works about Sentiment Analysis (SA) studying the task of identifying the polarity, whether the opinion expressed in a text is positive or negative about a given topic. However, most of research is focused on English texts and there are very few resources for other languages. In this work we present an Opinion Corpus for Arabic (OCA) composed of Arabic reviews extracted from specialized web pages related to movies and films using this language. Moreover, we have translated the OCA corpus into English, generating the EVOCA corpus (English Version of OCA). In the experiments carried out in this work we have used different machine learning algorithms to classify the polarity in these corpora showing that, although the experiments with EVOCA are worse than OCA, the results are comparable with other English experiments, since the loss of precision due to the translation is very slight.
The results showed that they are comparable to other English experiments, since the loss of precision due to the translation process is very slight, as can be seen in REF .
Bilingual Experiments with an Arabic-English Corpus for Opinion Mining
RANLP
Computer Science