Automated Social Media Mining System in Health Care

Abstract: Social media, by its nature, will bring different individuals with different experiences and viewpoints. Extracting knowledge from social media has great applications. In health care area, the advent in social media has created greater improvements in communicating. The users of social media post comments regarding different diseases and their remedies with the users' experiences in this regard. This could be so informative to other users as well. Others could get an overview regarding the diseases and their treatments. Taking the effect of social media into consideration, the information could reach a mass population. Sentiment analysis is the major focus here. Hence data preprocessing is a requisite. This is followed by the network modeling and side effect terms extraction. Through these the comments being considered for information extraction could be worth enough.

Keywords: Sentiment Analysis, Term Frequency, Inverse Document Frequency Scores, Data Pre-processing, Text Mining, Self Organizing Map.