  The ability to extract public opinion from web portals such as review sites,
social networks and blogs will enable companies and individuals to form a view,
an attitude and make decisions without having to do lengthy and costly
researches and surveys. In this paper machine learning techniques are used for
determining the polarity of forum posts on kajgana which are written in
Macedonian language. The posts are classified as being positive, negative or
neutral. We test different feature metrics and classifiers and provide detailed
evaluation of their participation in improving the overall performance on a
manually generated dataset. By achieving 92% accuracy, we show that the
performance of systems for automated opinion mining is comparable to a human
evaluator, thus making it a viable option for text data analysis. Finally, we
present a few statistics derived from the forum posts using the developed
system.
