Text Classification of Digital Forensic Data

Authors

Chrisitan Sunday Nwankwo, Georgia Southern UniversityFollow
Hayden Wimmer, Georgia Southern UniversityFollow
Lei Chen, Georgia Southern UniversityFollow
Jongyeop Kim, Georgia Southern UniversityFollow

Document Type

Conference Proceeding

Publication Date

12-22-2020

Publication Title

2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Proceedings

DOI

10.1109/IEMCON51383.2020.9284913

ISBN

978-1-7281-8416-6

ISSN

2644-3163

Abstract

This research aims to propose a model to classify text messages that extracted from the smart phone using forensic software and several machine learning algorithms. The data analysis procedure subdivided into physical extraction, relevant partitions, logical extraction, digital forensic analysis, and text classification. In the text classification step, the final result derived by applying sentiment analysis and k-means clustering algorithm under the control of python application. Through this model, we were able to classify most of the messages correctly as either being positive or negative.

Recommended Citation

Nwankwo, Chrisitan Sunday, Hayden Wimmer, Lei Chen, Jongyeop Kim. 2020. "Text Classification of Digital Forensic Data." 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Proceedings: 661-667: IEEE Xplore. doi: 10.1109/IEMCON51383.2020.9284913 source: https://ieeexplore.ieee.org/document/9284913/keywords#keywords isbn: 978-1-7281-8416-6
https://digitalcommons.georgiasouthern.edu/information-tech-facpubs/144

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