Twitter is one of the most popular social networking platforms of today’s generation and is a fundamental tool in harvesting the data of many users worldwide. Many discussions ranging from current affairs, news sharing, filing complaints to advertising and discussing some common interests etc. happen on Twitter. It is widely used by many famous politicians as a prominent communication medium to address large masses ,owing to its mass usage and popularity . Thus, it is safe to assume that people communicate their political ideologies on Twitter. Many works have been done so far to deduce the stance of user towards a particular party by performing sentiment analysis on their tweets using popular classifiers. To find connected and similar users, earlier works generated a social network graph, based on the assumption that friends and followers share similar interests, which might not be true in all cases. In contrast, the proposed work employs the concept of ensemble classifier (a single classifier generated from several base learning classifiers) to analyze the tweets and makes use of multiple interaction elements like followers/ following, mentions, re-tweets ,hash tags etc. to infer which political party a user identifies with. These interaction elements project out the homophily (users who share same beliefs and choices) amongst the users. The proposed study can be encompassed to any domain and can be used by advertising agencies, marketing companies, e-commerce, heath care etc. to identify their target audience.