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Award Abstract #1209359

Integrated Social History Environment for Research (ISHER)-Digging into Social Unrest

NSF Org: SMA
SBE Off Of Multidisciplinary Activities
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Initial Amendment Date: December 19, 2011
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Latest Amendment Date: December 19, 2011
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Award Number: 1209359
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Award Instrument: Standard Grant
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Program Manager: Patricia White
SMA SBE Off Of Multidisciplinary Activities
SBE Direct For Social, Behav & Economic Scie
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Start Date: January 1, 2012
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End Date: December 31, 2014 (Estimated)
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Awarded Amount to Date: $125,000.00
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Investigator(s): Dan Roth danr@illinois.edu (Principal Investigator)
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Sponsor: University of Illinois at Urbana-Champaign
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CHAMPAIGN, IL 61820-7473 (217)333-2187
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NSF Program(s): DiD Challenge
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Program Reference Code(s):
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Program Element Code(s): 8677

ABSTRACT

Social historians and researchers in social sciences rely to a great extent on text data for their research. Currently these data sources are increasingly available in electronic form. The Digging into Social Unrest project aims to develop software tools for automated analysis of news archives. The project will help researchers discover information and obtain answers to questions that now take large, if not unrealistic amounts of human effort to answer. The aim is to develop text mining tools which will provide social historians and scientists the means to detect, associate, and visualize the events and the underlying trends, people, and organizations related to social unrest.

This work is based on the notion that conditions leading to social unrest can be identified and extracted from news archives, which may include reports about events of varying degrees of organization and violence --ranging from social movement meetings, to protests, strikes, demonstrations, and riots. Careful study of these sources can be used to extract indicators analysts can use to predict societal instability trends and events.

The Digging into Social Unrest project will develop a text-mining based search system that improves entity and event extraction by building upon tools and services previously developed by members of this team. The tool, called ISHER (for Integrated Social History Environment for Research) will be a fully open source framework and will be designed with the intent of working on any digital text repository. Specifically, the tool will allow rich semantic metadata extraction for collection indexing, clustering, and classification.

The primary broader impact of this project is that it will develop a tool that can be used by a wide array of disciplines in the social sciences and humanities. In addition, the research will add to the body of knowledge on social unrest and is highly likely to spur research on comparable data archives by researchers in other fields.

This grant was made as part of the Digging Into Data Challenge, an international competition designed to foster research collaboration across countries and to encourage innovative approaches to analyzing large data sets in the social sciences and humanities. In addition to the US research team, this project includes researchers from the Netherlands and the United Kingdom.


PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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H. Peng and D. Khashabi and Dan Roth. "Solving Hard Coreference Problems," NAACL, the North American Conference of ACL, v.2015, 2015.

Q. Do and W. Lu and D. Roth. "Joint Inference for Event Timeline Construction," EMNLP, The conference on Empirical Methods in NLP, v.2012, 2012.

R. Zhao and Q. Do and D. Roth. "A Robust Shallow Temporal Reasoning System," NAACL, the North American conference of the ACL, Demo Track., v.2012, 2012.

W. Lu and D. Roth. "Automatic Event Extraction with Structured Preference Modeling," ACL, the Conference of the Association of Computational Linguistics, v.2012, 2012.

H. Wu and Z. Fei and A. Dai and S. Mayhew and M. Sammons and D, Roth. "IllinoisCloudNLP: Text Analytics Services in the Cloud," LREC, The Language Resource Project, v.2014, 2014.

H. Peng and K. Chang and D. Roth. "A Joint Framework for Coreference Resolution and Mention Head Detection," CoNLL, the Conference on Natural Language Learning, 2015, v.2015, 2015.

H. Peng, Y. Song, S. Upadhyay, C.-T. Tsai, M. Sammons, P. Reddy, S. Roy, and Dan Roth,. "Illinois CCG TAC 2015 Event Nugget, Entity Discovery and Linking, and Slot Filler Validation Systems," Text Analysis Conference (TAC), v.2015, 2015.

3. M. Sammons, Y. Song, R. Wang, G. Kundu, C.-T. Tsai, S. Upadhyay, S. Mayhew, S. Ancha, and D. Roth,. "Overview of UI-CCG Systems for Event Argument Extraction, Entity Discovery and Linking, and Slot Filler Validation," Text Analysis Conference (TAC), v.2014, 2014.

 

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