In view of the fact that an exponential growth in social networks is observed in last two decades. The opinion of the people about any political or non-political issues are now directly affected by the information shared on these social media. In any democratic nation the winning of any political party in general elections can be ensure depending upon its popularity on the electronic social networks, where large quantity of messages are shared in every unit of the time. Data available on the these social networking sites can be used for the forecasting the popularity of the political parties regular bases. In this paper, a simple logistic data model is applied on the data collected from Twitter, facebook and other media during the time of elections and opinion can be analyzed based classification of data on bases of high and low popularity parties during elections. The results of our data model are very stimulating and good for the analysis.