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Person-Centered Predictions of Psychological Constructs with Social Media Contextualized by ...

on YouTube 06m
Talkat UbiComp 2021 · 2021-09-21..09-26· [machine-learning, data-visualization]

speakers

name:Koustuv Saha
links:none on file
name:Ted Grover
links:none on file
name:Stephen M. Mattingly
links:none on file
name:Vedant Das Swain
links:none on file
name:Pranshu Gupta
links:none on file
name:Gonzalo J. Martinez
links:none on file
name:Pablo Robles-Granda
links:none on file
name:Gloria Mark
links:none on file
name:Aaron Striegel
links:none on file
name:Munmun De Choudhury
links:none on file

resources

video:https://youtu.be/frmQOr2uO6I
slides:none on file

summary

Uses multimodal sensing (Bluetooth, wearables, phone) plus Facebook language from 754 participants to build cluster-specific models; hierarchical clustering yields three behavioral clusters and models are evaluated with five-fold CV and a held-out set of 50 participants. Contextualized models improve prediction of personality traits, anxiety, and sleep quality, leave affect unchanged, and worsen cognitive ability prediction. Code uses standard ML comparisons and pooled Pearson/S-MAPE metrics, showing personalization helps when constructs link to physical behavior.

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