This paper reports on a generalizable system model design that analyzes the unstructured customer reviews inside the posts about electronic products on social networking websites. For the purposes of this study, posts on social networking websites have been mined and the keywords are extracted from such posts. The extracted keywords and the ontologies of electronic products and emotions form the base for the sentiment analysis model which is used to understand online consumer behavior in the market. In order to enhance system accuracy, negating and enhancing terms are considered in the proposed model. Sentiment analysis is demonstrated to be extremely important to system accuracy.