User Engagement
User engagement research focuses on understanding and optimizing how users interact with digital systems, aiming to improve satisfaction, retention, and overall experience. Current research emphasizes personalized approaches, leveraging techniques like reinforcement learning, temporal graph networks, and transformer models to predict and adapt to individual user behavior and preferences across diverse platforms, from social media to e-commerce and mHealth applications. These advancements have significant implications for improving the design and efficacy of various digital products and services, informing the development of more engaging and effective interfaces.
Papers
Words That Stick: Predicting Decision Making and Synonym Engagement Using Cognitive Biases and Computational Linguistics
Nimrod Dvir, Elaine Friedman, Suraj Commuri, Fan Yang, Jennifer Romano
A Predictive Model of Digital Information Engagement: Forecasting User Engagement With English Words by Incorporating Cognitive Biases, Computational Linguistics and Natural Language Processing
Nimrod Dvir, Elaine Friedman, Suraj Commuri, Fan yang, Jennifer Romano