Search Results for author:
Found 3 papers, 1 papers with code
Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline
To address this concern, in Study 1, we collected linguistic data from N=35 high socially anxious participants in a variety of social contexts, finding that digital linguistic biomarkers significantly differ between evaluative vs. non-evaluative social contexts and between individuals having different trait psychological symptoms, suggesting the likely importance of personalized approaches to detect state anxiety.
Gaussian Latent Dirichlet Allocation for Discrete Human State Discovery
In this article we propose and validate an unsupervised probabilistic model, Gaussian Latent Dirichlet Allocation (GLDA), for the problem of discrete state discovery from repeated, multivariate psychophysiological samples collected from multiple, inherently distinct, individuals.
Connections between Relational Event Model and Inverse Reinforcement Learning for Characterizing Group Interaction Sequences
We demonstrate the special utility of IRL in characterizing group social interactions with an empirical experiment, in which we use IRL to infer individual behavioral preferences based on a sequence of directed communication events from a group of virtual-reality game players interacting and cooperating to accomplish a shared goal.
