Crime analysis and forecasting on spatio temporal news feed dataan indian context

Title

Crime analysis and forecasting on spatio temporal news feed dataan indian context

Creator

Prathap B.R.; Krishna A.V.N.; Balachandran K.

Description

Social media is a platform where people communicate, interact, share ideas, interest in careers, photos, videos, etc. The study says that social media provides an opportunity to observe human behavioral traits, spatial and temporal relationships. Based on study Crime analysis using social media data such as Facebook, Newsfeed articles, Twitter, etc. is becoming one of the emerging areas of research across the world. Using spatial and temporal relationships of social media data, it is possible to extract useful data to analyse criminal activities. The research focuses on implementing textual data analytics by collecting the data from different news feeds and provides visualization. This researchs motivation was identified based on relevant work from different social media crime and Indian government crime statistics. This article focuses on 68 types of different crime keywords for identifying the type of crime. Nae Bayes classification algorithm is used to classify the crime into subcategories of classes with geographical factors, and temporal factors from RSS feeds. Mallet package is used for extracting the keywords from the news-feeds. K-means algorithm is used to identify the hotspots in the crime locations. KDE algorithm is used to identify the density of crime, and also our approach has overcome the challenges in the existing KDE algorithm. The outcome of research validated the proposed crime prediction model with that of the ARIMA model and found equivalent prediction performance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Source

Studies in Big Data, Vol-90, pp. 307-327.

Date

2021-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Crime analysis; Crime density; Crime prediction; Hotspot detection; Social media

Coverage

Prathap B.R., Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Krishna A.V.N., Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Balachandran K., Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 21976503

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1007/978-3-030-74575-2_16

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111615173&doi=10.1007%2f978-3-030-74575-2_16&partnerID=40&md5=a159e2c545285b18d406580343a5ccb5