Publication

Abstract : Social media facilitates the users to exchange their opinion, thoughts and ideas. The advantage of sharing an information through social media is, it will widespread the content quickly. There are so many social media platforms among which Twitter is one of them. Through twitter the user can communicate the information briefly. So many real-world issues are discussed on twitter, in which the discussion about HIV/AIDS is ranked as one of the topmost topics. Due to the advancement of social media many users have come forward to discuss about this societal topic. These kinds of discussion will help the communication campaigns to promote better HIV/AIDS education. In this work tweets were collected by the keywords including HIV and AIDS. Following the pre-processing steps, feature extraction has been carried out. Feature extraction is very crucial step in mining twitter because the data is in unstructured format. So, increasing the efficiency of feature extraction will improve the outcome of classification task. In this work an efficient feature extraction method has been proposed which gives a better result when compared to existing.