Social Technologies Lab

We design, build, and study systems that support social interactions in online and physical spaces

Social Technologies Lab

About Us

We design, build, and study systems that support social interactions in online and physical spaces.

We utilize a variety of methods from mining data on social media to conducting controlled experiments to interviewing users. Our work aims to understand the significance of people’s digital traces and to leverage this information for positive social good.

We are part of Jacobs Institute’s Connective Media hub at Cornell Tech. Some of our research is conducted within the Connected Experiences Lab. If you are interested in working with us, please get in touch by contacting us below!

News

  • 1/2021

    VoterFraud2020 dataset has been released. Learn more at VoterFraud2020.io.

  • 1/2021

    We have a new paper in ACM CSCW 2021 on AI-Mediated Communication - read it here!

  • 9/2019

    We've received an NSF award to study AI-Mediated Communication and trust.

Projects

  • Locally-Connected Experiences

    As part of the AOL Connected Experiences Laboratory, we look at how data from mobile devices, sensors, as well as new cryptographic techniques and protocols can enable a socio-technical infrastructure to provide awareness, trust and meaningful connections between physically co-located individuals, including buildings, offices, and public spaces. Such infrastructure will empower people to make better connections and communication in their local communities, with long term impact on participation and democracy.

  • Attention to Online Media

    The goal of this project is to advance our understanding of the psychological mechanisms behind people's attention, as reflected through their interactions with digital content. In particular, we focus on the context of actions that people takeonline without any experimental intervention and examine how context affects behavior. We draw on theories from a wide range of fields to address questions that pertain to individual's attention to content, expectations for attention from others and the value in getting that attention. To that end, we harness machine learning methods as well as language and statistical modeling to analyze signals of human attention as they occurs naturally outside of lab settings.

Publications

Contact

We're located at Cornell Tech. Come by and say hi (when public health conditions permit)!

2 W Loop Rd
New York, NY
Cornell Tech

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