Grant Number: 439105
- Description: Standard Grant
- Associated Project:
- Award Date:
- Award Period: 2004-09-01 to 2006-08-31
- Amount: $ 34638.00
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This is a collaborative grant with two PIs; Javed Mostafa of Indiana, and David Stark of Columbia.
With a grant from the NSF Digital Government Program, David Stark has been studying the role of information technologies in the public debate surrounding the rebuilding of Lower Manhattan in the wake of the September 11 attacks on the World Trade Center. In the process of conducting that research Stark's team has assembled an extensive digital archive containing 5,000 participant oral statements from one town hall meeting and an additional 19,000 oral statements collected at 240 different venues around New York City in the 'Imagine New York Envisioning Workshops'. These gathered statements provide a rich opportunity for testing various strategies of computer-assisted interpretation because they provide an opportunity to compare the conceptual patterns discerned by human intelligence with findings reached through the analytical methods of artificial intelligence. Supporting the initial explotation of that archive is the purpose of this grant.
The technical component of this grant arises from work Javed Mostafa has done under an NSF ITR grant. Data mining research concentrating on spontaneous human conversations is at an early stage of development. Mostafa's approach to data mining can offer different ways to analyze the same data. The project has three specific goals: 1) to detect emergent concepts by applying techniques that do not impose any a priori conditions; 2) to use techniques for analyzing known concepts by applying constraints on the mining process, and 3) to develop visualization of the results to facilitate interpretation by social scientists and support direct validation by citizen participants.
Computer mediated communication offers new channels for citizens to express their views to elected officials and government agencies. Often, the resulting deluge of comments poses a technical and political challenge. How can officials/agencies make sense of large-scale citizen input? How can meaningful patterns be efficiently and effectively identified? This project will contribute to advancing understanding of the opportunities and the limitations of computer-assisted interpretation. Its findings will be of considerable interest to scholars as well as to government managers responsible for the rebuilding of lower Manhattan.
Many challenges involved in creating new data mining tools demands an interdisciplinary collaboration for access to new data; this project offers such an opportunity. This time-critical testing of artificial intelligence methods will be important in understanding the public input to rebuilding lower Manhattan.