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Sentiment Analysis of Tweets for Estimating Criticality and Security of Events
Abstract
Social Media has become one of the major industries in the world. It has been noted that almost three fourth of the world's population use social media. This has instigated many researches towards social media. One such useful application is the sentimental analysis of real time social media data for security purposes. The insights that are generated can be used by law enforcement agencies and for intelligence purposes. There are many types of analyses that have been done for security purposes. Here, the authors propose a comprehensive software application which will meticulously scrape data from Twitter and analyse them using the lexicon based analysis to look for possible threats. They propose a methodology to obtain a quantitative result called criticality to assess the level of threat for a public event. The results can be used to understand people's opinions and comments with regard to specific events. The proposed system combines this lexicon based sentimental analysis along with deep data collection and segregates the emotions into different levels to analyse the threat for an event.
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