NDLI: On a framework for the prediction and explanation of changing opinions

Content Provider	IEEE Xplore Digital Library
Author	Santos, E.E. Santos, E. Wilkinson, J.T. Huadong Xia
Copyright Year	2009
Description	Author affiliation: Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060 (Santos, E.E.; Huadong Xia) \|\| Thayer School of Engineering Dartmouth College, Hanover, NH 03755 (Santos, E.; Wilkinson, J.T.)
Abstract	One of the greatest challenges in accurately modeling a human system is the integration of dynamic, fine-grained information in a meaningful way. A model must allow for reasoning in the face of uncertain and incomplete information and be able to provide an easy to understand explanation of why the system is behaving as it is. To date, work in multi-agent systems has failed to come close to capturing these critical elements. Much of the problem is due the fact that most theories about the behavior of such a system are not computational in nature, they come from the social sciences. It is very difficult to successfully get from these qualitative social theories to meaningful computational models of the same phenomena. We focus on analysis of human populations where discerning the opinions of the members of the populace is integral in understanding behavior on an individual and group level. Our approach allows the easy aggregation and de-aggregation of information from multiple sources and in multiple data types into a unified model. We also present an algorithm that can be used to automatically detect the variables in the model that are causing changes in opinion over time. This gives our model the capability to explain why swings in opinion may be experienced in a principled, computational manner. An example is given based on the 2008 South Carolina Democratic Primary election. We show that our model is able to provide both predictions of how the population may vote and why they are voting this way. Our results compare favorably with the election results and our explanation of the changing trends compares favorably with the explanations given by experts.
Starting Page	1446
Ending Page	1452
File Size	838187
Page Count	7
File Format	PDF
ISBN	9781424427932
ISSN	1062922X
DOI	10.1109/ICSMC.2009.5346294
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Nominations and elections Multiagent systems Voting Knowledge representation Predictive models Computational modeling Bayesian methods Cybernetics USA Councils probability theory Bayesian Knowledge Bases multi-agent system
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
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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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