Sentiment analysis is a well known technique for finding sentiments from text data without any human intervention. Sentiment analysis shows various methods for implementation. This is the paper which suggests new approach towards classification of sentiments which are present in textual content. To support Hidden Markov Model it suggests some transition rules for model rather than transition probability. It effectively uses part of speech tagging for formation of transition rules.