NDLI: Leveraging sociological models for prediction I: Inferring adversarial relationships

Content Provider	IEEE Xplore Digital Library
Author	Colbaugh, R. Glass, K.
Copyright Year	2012
Description	Author affiliation: New Mexico Institute of Mining and Technology, Socorro, USA (Glass, K.) \|\| Sandia National Laboratories, Albuquerque, NM USA (Colbaugh, R.)
Abstract	There is considerable interest in developing techniques for predicting human behavior, for instance to enable emerging contentious situations to be anticipated or permit the nature of ongoing but “hidden” activities to be inferred. A promising approach to this problem is to collect appropriate empirical data and then apply machine learning methods to the data to generate the predictions. This two-part paper shows that the performance of such learning algorithms often can be improved substantially by leveraging sociological models in their development and implementation. In particular, we demonstrate that sociologically-grounded learning algorithms outperform gold-standard methods in two important and challenging tasks: 1.) inferring the (unobserved) nature of relationships in adversarial social networks, and 2.) predicting whether nascent social diffusion events will “go viral”. Significantly, the new algorithms perform well even when there is limited data available for their training and execution.
Starting Page	66
Ending Page	71
File Size	519689
Page Count	6
File Format	PDF
ISBN	9781467321051
e-ISBN	9781467321044
DOI	10.1109/ISI.2012.6284093
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Accuracy Social network services Heuristic algorithms social networks Predictive models Prediction algorithms Classification algorithms machine learning predictive analysis sociological models
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
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
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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