| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | April 20, 2021 |
| Latest Amendment Date: | August 13, 2024 |
| Award Number: | 2046590 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Hector Munoz-Avila
hmunoz@nsf.gov (703)292-4481 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | May 1, 2021 |
| End Date: | April 30, 2026 (Estimated) |
| Total Intended Award Amount: | $517,484.00 |
| Total Awarded Amount to Date: | $517,484.00 |
| Funds Obligated to Date: |
FY 2022 = $101,226.00 FY 2023 = $220,332.00 FY 2024 = $102,950.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
4400 VESTAL PKWY E BINGHAMTON NY US 13902 (607)777-6136 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
NY US 13902-6000 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Info Integration & Informatics |
| Primary Program Source: |
01002425DB NSF RESEARCH & RELATED ACTIVIT 01002223DB NSF RESEARCH & RELATED ACTIVIT 01002324DB NSF RESEARCH & RELATED ACTIVIT 01002526DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
This project promotes the progress and advancement of scientific knowledge by exploring new
methods for understanding and modeling online sentiment. As the Web has become critical to
society, impacting our personal lives as well as the world at large, a greater need to understand
how people interact. In particular, research into how to measure people?s opinion on various
topics or types of content has failed to address the new ways and types of content used on the
evolving social Web. This project addresses this lack of understanding by developing new tools
to help quantify online sentiment using large-scale, empirical data. In addition to these new
tools, output from the project, including datasets and code artifacts will help other researchers
advance our understanding of social media.
In this project, the investigator seeks to achieve four research objectives. The first is the
creation of a multi-platform social media dataset. In particular, the investigator will develop a
series of tools leveraging prior experience in large-scale data collection to perform continuous
identification and collection of multimedia data from emerging social media platforms. Next, the
investigator will develop data-driven techniques to understand coded language used in social
media. These techniques will focus not just on textual content, e.g., slang words, but also coded
visual language, e.g., memes. The third objective is developing a new, explainable system for
rating the sentiment of content. This method departs from existing approaches by treating the
classification task as a game between two pieces of content and learning a total ordering of the
content devised from the Elo rating system used in chess and video games. Finally, the
investigator will explore user and community level modeling of online sentiment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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