Spatio-Temporal Analysis of Archived Web News for Precise Political Event Detection and Impact Analysis in India's Southern States

Abstract

The national political system has the directly impacts the economy. Every political party has their own economic policies. This has the major impact on the economic stability of the nation. Sometimes, few political parties rule either the state or national Governments. Their policies directly reflect in the state or national level financial systems. In general political parties, pay more attention to the state in which they control or aspire to establish their party's rule. Political discourse has an unspoken impact on the state's financial stability. Data from unstructured political events (1200 records) produced for accurate political event prediction; data was pulled from the archives of web news accumulated over the last 5 years to better understand the impact of such impact discovered in this article. This recommended work includes the advantages of Spatiotemporal Analysis of Web News Archives for forecasting network features modeled through political events and converting them into possible information based on natural language processing qualities. The suggested approach constructs a spatial analysis based on hotspots for estimating the sequence of political events in India. Lastly, the resulting data is nurtured into several classifiers for a more reliable prediction and identification procedure. This proposed technique reached a maximum frequency of 78.21 percent and 93.58 percent, respectively, when compared to the Random forest method and the K-neighbor neighbour (KNN) algorithms.