Predicting Depression with Social Media Images

Stankevich Maxim; Nikolay Ignatiev; Ivan Smirnov; Ivan Smirnov

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Paper

Predicting Depression with Social Media Images

Topics: Classification and Clustering; Feature Selection and Extraction; Image and Video Analysis and Understanding

In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 235-240, 2020 , Valletta, Malta

Authors: Stankevich Maxim ¹ ; Nikolay Ignatiev ² and Ivan Smirnov ^{1

;

2}

Affiliations: ¹ Federal Research Center ”Computer Science and Control” of RAS, Moscow, Russia ; ² RUDN University, Moscow, Russia

Keyword(s): Machine Learning, Classification, Depression, Social Media, Image Recognition.

Abstract: The study is focused on the task of depression detection by analyzing images related to social media users. We formed a dataset that consists of 485,121 images from profiles of 398 volunteers that provided access to their data in popular Russian-speaking social media Vkontakte. The results of the depression questionnaire were used to distinguish depression and control groups and set the binary classification task. We observed 3 types of users’ images: profile photos, images from posts, and albums. We applied object detection methods to retrieve object features that determine the presence of 80 different object classes on users’ images. To aim the task, the different machine learning algorithms were trained on the objects and color features. Our models achieved up to 65.5% F1-score for the task of revealing depressed users.

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Paper citation in several formats:

Maxim, S.; Ignatiev, N. and Smirnov, I. (2020). Predicting Depression with Social Media Images. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-397-1; ISSN 2184-4313, SciTePress, pages 235-240. DOI: 10.5220/0009168602350240

@conference{icpram20,
author={Stankevich Maxim. and Nikolay Ignatiev. and Ivan Smirnov.},
title={Predicting Depression with Social Media Images},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2020},
pages={235-240},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009168602350240},
isbn={978-989-758-397-1},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Predicting Depression with Social Media Images
SN - 978-989-758-397-1
IS - 2184-4313
AU - Maxim, S.
AU - Ignatiev, N.
AU - Smirnov, I.
PY - 2020
SP - 235
EP - 240
DO - 10.5220/0009168602350240
PB - SciTePress