Sentimental Analysis is the best way to judge people's opinion regarding a particular post. In this paper we present analysis for sentiment behavior of Twitter data. The proposed work utilizes the naive Bayes and fuzzy Classifier to classify Tweets into positive, negative or neural behavior of a particular person. We present experimental evaluation of our dataset and classification results which proved that combined proposed method is more efficient in terms of Accuracy, Precision and Recall.
This paper proposed a Clustering approach based routing protocol for VANETs. The proposed algorithm is a distributed clustering algorithm together with OLSR Routing protocol, which possesses excellent Data dissemination rate, where Data dissemination is defined by throughput of protocol. In addition, the algorithm is also perform excellent in terms of End to End delay and exhibits a reasonable overhead. The algorithm is achieved by utilizing a new clustering technique based protocol called OLSR-C (OC). The clustering scheme uses a vehicle's position (provided by GPS) and velocity information to form clusters with low relative mobility between the cluster heads and their cluster members.