Main Article Content
Abstract
The social nuisance is an inhuman act of the individual causing damage to the whole community and burdens the society which is punishable by law. Structuraldata mining followed by entiment analysis on online social media helps to detect the grievance patterns on texts. Taking on social networking sites, enables users to post their viewsand convey information about the author. Electronic media allows extraction of information and data from various databases which combines solutions from various fields. Aggregating and integrating the data to judge the opinion uses geospatial analysis which establishes correlations between the posts and crimes in various cities and towns.
Sentiment analysis techniques has to be conducted to analyse the vocabulary and intensity of grievance of a post of a particular location which reveals the crime rate of a location in real-time and helps to detect the patterns of crime. When analysing data, natural languageprocessing techniques are used to process the unorganised data. They have to be refined by the experts making it clear. For the data analytics we employ machine learning techniques to create a traditional programming on the data automation. We employ machine learning algorithms for