Sentiment analysis is a tool to identify and measure the emotion in a piece of text. Negation handling is an important aspect of natural language processing(NLP) for Twitter data. In this article, a negation handling technique using Convolutional Neural Networks (CNNs) model for classification is proposed. The system is evaluated on SemEval-2017 dataset. The classification performance is improved by using CNN on the negative tweets. The paper compares the performance of ANNs and CNNs in handling negation words and evaluates them on the tweets data. The proposed negation strategy attains a superior performance accuracy over machine learning models by preventing misclassified tweets.