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!


  • 9/2016

    Five papers by lab authors accepted to CSCW 2017 -- PDFs available soon!

  • 5/2016

    “Changes in Engagement Before and After Posting to Facebook” Honorable Mention for Best Paper at CHI 2016

  • 4/2016

    Paper studying view duration of YouTube videos to appear in ICWSM; the paper and dataset are both available below


  • 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 take online 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.



We're located at Cornell Tech. Come by and say hi!

111 8th Ave
Suite #1202
New York, NY
Cornell Tech

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