Toward Predictive Crime Analysis via Social Media, Big Data, and GIS Spatial Correlation

Corso, Anthony Joseph

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https://hdl.handle.net/2142/73457 Copy

Description

Title

Toward Predictive Crime Analysis via Social Media, Big Data, and GIS Spatial Correlation

Author(s)

Corso, Anthony Joseph

Issue Date

2015-03-15

Keyword(s)

• natural language processing
• social media
• information systems

Abstract

To support a dissertation proposal a link between social media, incident-based crime data, and data of public domain needed to be verified. A predictive crime-based artifact utilizing data mining and natural language processing techniques commingled with graphical information system architecture is complex. With respect to social media, an attempt was made to observe such an artifact’s data flexibility, process control, and predictive capabilities. Data and their capabilities were observed when preprocessing social media’s noisy data, government-based structured data, and obscurely collected field data for use in a predictive GIS artifact. To support project goals the approach for artifact design, data collection, and discussion of results was couched as an exploratory study. Results indicate a link between social media data and domain specific datasets exist. Questions for further observation and research deal with processing the subtle differences between structured and noisy data, weighted social media input layers, and time-series analysis.

Publisher

iSchools

Series/Report Name or Number

iConference 2015 Proceedings

Type of Resource

text

Language

English

Permalink

http://hdl.handle.net/2142/73457

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Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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