Inflammable Intention Detector for Social Media

These days, the influence of internet media is significant not just in our lives but also in society as a whole. Web-based media may have been responsible for the effective, rapid, and faceless dissemination of contempt in recent times. It is therefore necessary to cultivate an automatic model that is capable of recognizing such stuff. It is possible for the study that is being suggested to identify hate speech in tweets. A performance evaluation of machine learning models is presented in the proposed study. This evaluation is accomplished by using various optimizers, and it also includes a recommended approach that involves picking the models that perform the best. The results are based on the size of the datasets, their properties, and how efficient they are. We have implemented a model that is based on triple layer fusion in order to improve the learning rate and optimize the system. For the purpose of improving both efficiency and precision, we have utilized the Grid search method.