Abstract
Given the booming expansion of social media, it is not surprising that the ¬eld of sentiment analysis has seen advancements rapidly in recent years. Nevertheless, the use of sentiment analysis is quite limited in the ¬eld of transportation to assess the safety of an area. This research paper propose the sentiment analysis of tra c or crime information as a new way to handle this problem. To achieve this, we have used one of the user generated contents i.e. Twitter as our source of information. Twitter has emerged as an essential new tool to make social measurements. Millions of tweeps express their thoughts and sentiments about any topic imaginable on daily basis voluntarily. This heap of data is quite signi¬ficant from both research and business perspectives. Thus, we intend to design an application through our research with which the categorization of data publically available at Twitter can be done, so that the users can have access to the customized and useful information related to the areas they are planning to visit. To carry out this research practically, data from Twitter was collected for a particular source and destination and sentiment analysis was performed using SentiWordNet. The result yielded in overall polarity of the tweets informing users about the safety of all the available routes. This study will help greatly in the development of intelligent transportation systems and our experimental results demonstrate the effectiveness of the system.