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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Texas At El Paso |
| Country | United States |
| Start Date | Oct 01, 2024 |
| End Date | Mar 31, 2026 |
| Duration | 546 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2451946 |
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).
Links between people in Online Social Networks (OSNs) have been used by attackers to access private and sensitive user data, post false or abusive information on the timelines and news feeds of victims, and scam and influence the perceptions of victims. The massive growth of social media usage has incentivized perpetrators to connect users through fake "sockpuppet" accounts, an attack that is often successful due to the lack of adequate verification of declared information.
The goal of this project is to significantly expand the understanding of identity deception and abuse in online social networks, and design and build intervention mechanisms to mitigate these types of attacks. The project team will work with social media users to create a digital framework that can assess users' risk of falling victim to sockpuppet attacks, educate them about these attacks, and help them carefully examine connection invites and avoid accepting invitations from suspicious accounts.
This goal is to develop a new generation of sockpuppet prevention solutions that have the potential to help protect millions of vulnerable OSN users from sexual predators, online fraudsters, scammers, adversaries, or malicious hackers.
This project will build a digital framework rooted in cognitive psychology, UX research, and machine learning methods to defend against sockpuppet connection requests in online social networks. In a first research thrust, the researchers will develop survey instruments and user studies to investigate pending connection decisions, motivations, and behaviors in OSNs.
The findings from this research thrust will be utilized to develop the next thrust, where the researchers will implement a "spam connection" folder through a pending connection decision classifier. Finally, the researchers will ievelop a novel Online Social Network Pending Connection Processing Interface .This will be designed as a layer on top of existing social networks that can be used to administer and assess educational and interface interventions around sockpuppets in the context of real social networks, while allowing the research team to address ethical and legal considerations of working with sockpuppet connections and people's private data.
Together, this work will both enhance the understanding of just-in-time motivations and behaviors related to social network risks and help sociologists gain deeper insights from underexplored social and spatial dimensions provided by social networks to test relevant theories.
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.
University of Texas At El Paso
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