In the present day, circumstances now-a-days, the scope of short text such as Twitter messages, blogs, chat massages, book and movie summaries, forum, news feeds, and customer review is increasing very drastically. These applications pose a tremendous challenge to the text classifications due to sparseness of the relevant data & lack of similarity between the words. Short text classification is nothing but a process of assigning various input short texts to one or more target categories based on its contents. Here, the authors compared various algorithms such as support vector machine, naive bayes, K-nearest neighbor, etc.