Sentiment Analysis (SA) is an ongoing field of research in text mining field. SA is the computational treatment of opinions, sentiments and subjectivity of text. [1] The Comments which is given by the viewers/non-viewers of the program that reflect whether the program is positive (positive incremental) or negative (negative decrement) or neutral. SA can be analyzing the given text into predefined categories as positive, incremental positive, negative, decrement negative or neutral based on the sentiment terms that appear with in the opinionated documents. These comments need to be explored, analyses and organized for better decision making. The earlier related researcher not enough consider the POS tagging which is very important to identify the polarity of the sentiment. And did not consider the irony and stairs of expressions. And also they only considered positive and negative polarities but important to consider the inverter words that will change the polarity. In our paper the gaps basically held by using NLP Techniques. Sentiment analysis system applied to solve the polarity by using Rule based and Dictionary approach. The comments collected from the viewers/non-viewers from website/Facebook page, focusing group discussion, and by distributing an open ended questioner. The experiments are conducted using 1022 (one thousands and twenty two) sentiment comments with four target research area. The average Accuracy, Precession, Recall and f-score respectably are 0.85, 0.95, 0.89 and 0.91. Experimental results using viewers of comments shows that the effectiveness of the system.