NDLI: Using Twitter Content to Predict Psychopathy

Content Provider	IEEE Xplore Digital Library
Author	Wald, R. Khoshgoftaar, T.M. Napolitano, A. Sumner, C.
Copyright Year	2012
Abstract	An ever-growing number of users share their thoughts and experiences using the Twitter micro logging service. Although sometimes dismissed as containing too little content to convey significant information, these messages can be combined to build a larger picture of the user posting them. One particularly notable personality trait which can be discovered this way is psychopathy: the tendency for disregarding others and the rule of society. In this paper, we explore techniques to apply data mining towards the goal of identifying those who score in the top 1.4% of a well-known psychopathy metric using information available from their Twitter accounts. We apply a newly-proposed form of ensemble learning, Select RUSBoost (which adds feature selection to our earlier imbalance-aware ensemble in order to resolve high dimensionality), employ four classification learners, and use four feature selection techniques. The results show that when using the optimal choices of techniques, we are able to achieve an AUC value of 0.736. Furthermore, these results were only achieved when using the Select RUSBoost technique, demonstrating the importance of feature selection, data sampling, and ensemble learning. Overall, we show that data mining can be a valuable tool for law enforcement and others interested in identifying abnormal psychiatric states from Twitter data.
Starting Page	394
Ending Page	401
File Size	239810
Page Count	8
File Format	PDF
ISBN	9781467346511
DOI	10.1109/ICMLA.2012.228
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Support vector machines ensemble learning psychopathy Neurons Psychology Vegetation Machine learning Twitter data sampling feature selection
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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