Laura Wendlandt, Rada Mihalcea, Ryan Boyd, James Pennebaker
Release date: April 9, 2018
Language and Information Technologies (LIT)
University of Michigan
The code in this repository was used in the paper "Multimodal Analysis and Prediction of Latent User Dimensions" by Wendlandt, et al. I have tried to document it well, but at the end of the day, it is research code, so if you have any problems using it, please get in touch with Laura Wendlandt (wenlaura@umich.edu).
We cannot release the data used in the paper because of privacy concerns.
If you use this code, please cite the following paper:
@inproceedings{Wendlandt17Multimodal,
author = {Wendlandt, L. and R. Mihalcea and R. Boyd and J. Pennebaker},
title = {Multimodal Analysis and Prediction of Latent User Dimensions},
booktitle = {Proceedings of the 9th International Conference on Social Informatics (SocInfo 2017)},
year = {2017},
address = {Oxford, UK}
}
This material is based in part upon work supported by the National Science Foundation (NSF #1344257), the John Templeton Foundation (#48503), and the Michigan Institute for Data Science (MIDAS). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF, the John Templeton Foundation, or MIDAS. We would like to thank Chris Pittman for his aid with the data collection, Shibamouli Lahiri for the readability code, and Steven R. Wilson for the implementation of Mairesse et al.