Abstract

Social media like Facebook today are not only just a website. They are now become much popular communication tool for internet users. It is a medium through which users belonging to any of category, profession can make their comments. These all comments have contained some features along with it. These comments or status are really useful which are actually viewed as their ‘OPINIONS’. Opinions are really important while we need to analyze any of product, topic, discussion and whatever which will require some user opinions to draw some inferences and conclusions from them. Social media plays an important role for this intention. In this paper we focused on facebook statuses, which we can view as opinions of users or their reaction on concern we want to analyze. We develop tool status puller that automatically collects random facebook statuses. Then we make classifier that performs classifications on that corpus collected from facebook. Our classifier is able to extract three features GOOD, BAD and AVERGAE from that statuses respectively. As per classifier results we perform evaluations experiments which further can be work for feature mining of user opinions on facebook. It’s pure new and unique technique proposed in the field of opinion mining.

How to Cite
AKASH SHRIVASTAVA, BHASKER PANT, Mr.. Opinion extraction and classification of real time Facebook Status. Global Journal of Computer Science and Technology, [S.l.], apr. 2012. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/544>. Date accessed: 18 jan. 2021.