- Collaboration with the Grow startup on feedback and digital nudging featured on Cornell Tech website - Cornell Tech Students Create a Platform for Personal Growth.
- Attended BIG DATA in Healthcare at the Weizmann Institute of Science in Israel.
- Research on recommendations discussed in a WIRED article - The People Trying to Make Internet Recommendations Less Toxic.
- Attended the Web Conference 2019 (WWW19) in San Fransisco
- Attended Big Data for Better Science: Technologies for Measuring Behaviour at the Royal Society.
- Research on digital wellbeing and digital nudging featured on Cornell Chronicle and Cornell Daily Sun.
We use digital nudging techniques to curb digital distraction and increase digital wellbeing. In one study we used mobile intervention that combines nudge theory and negative reinforcement to create a subtle, repeating phone vibration that nudges a user to reduce their digital consumption. This intervention reduced facebook usage by over 20%. We plan to episodically apply our interventions in specific everyday contexts such as education, sleep, and work.
We explore a personalization approach in which individuals actively harness their own digital traces to reframe personalization. We focus in particular on algorithms, systems, and rich user interactions that make personalization immersive, through the use of diverse personal data sources, and intentional, through transparency and user-modeling input that allows the end user to amplify their aspirational-behaviors relative to historically-observed behavior.
small data and Personalization
Small data are the myriad of digital traces we each generate everyday. Unfortunately, that data is often unavailable to us in a form that we can make sense of or act upon. Imagine a special kind of app running in the cloud that privately and securely turns your small data into big insights. Through our collaborations with researchers spanning healthcare, behavioral economics, human computer interaction and policy we collaborate to iteratively develop and evolve our services to address issues and problems in the real-world.
Beehive Research platform
Beehive is a research platform developed for the study of human behavior by leveraging the power of mobile ubiquitous technology. Using this platform, researchers will be able to recruit more participants, collect objective data and apply smart interventions to improve daily life, in the wild. Beehive seamlessly integrates with smartphones making it easy for participants to sign up for and participate in a study by using the mobile phone that is already in their pockets.
Behavioral Economics for Tech
Behavioral economics studies the effect of psychological, social, cognitive and emotional factors on humans decisions and behavior. This course will help students learn key concepts from behavioral economics and apply them in their daily lives, in the design of products, and in the research of human behavior. This course will explore the opportunities and challenges faced by researchers and practitioners when exploring the interplay between behavioral economics and technology.
- Longqi Yang, Michael Sobolev, Yu Wang, Jenny Chen, Drew Dunne, Christina Tsangouri, Nicola Dell, Mor Naaman, Deborah Estrin. How Intention Informed Recommendations Modulate Choices: A Field Study of Spoken Word Content. In the World Wide Web Conference (The Web Conference - WWW), 2019.
- Longqi Yang, Michael Sobolev, Christina Tsangouri, Deborah Estrin. Understanding User Interactions with Podcast Recommendations Delivered Via Voice. In the 12th ACM Conference on Recommender Systems (Recsys), 2018.
- Fabian Okeke, Michael Sobolev, Nicola Dell, and Deborah Estrin. Good Vibrations: Can a Digital Nudge Reduce Digital Overload?. In the International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI), 2018.
- Fabian Okeke, Michael Sobolev, Deborah Estrin. “Towards a Behavior Change Research Platform”. In the APA conference on Technology, Mind and Society, 2018.