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Detecting early signs of depression in the conversational domain: The role of transfer learning in low-resource scenarios ...
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Predicting subjective well-being in a high-risk sample of Russian mental health app users
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In: EPJ Data Sci (2022)
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Abstract:
Despite recent achievements in predicting personality traits and some other human psychological features with digital traces, prediction of subjective well-being (SWB) appears to be a relatively new task with few solutions. COVID-19 pandemic has added both a stronger need for rapid SWB screening and new opportunities for it, with online mental health applications gaining popularity and accumulating large and diverse user data. Nevertheless, the few existing works so far have aimed at predicting SWB, and have done so only in terms of Diener’s Satisfaction with Life Scale. None of them analyzes the scale developed by the World Health Organization, known as WHO-5 – a widely accepted tool for screening mental well-being and, specifically, for depression risk detection. Moreover, existing research is limited to English-speaking populations, and tend to use text, network and app usage types of data separately. In the current work, we cover these gaps by predicting both mentioned SWB scales on a sample of Russian mental health app users who represent a population with high risk of mental health problems. In doing so, we employ a unique combination of phone application usage data with private messaging and networking digital traces from VKontakte, the most popular social media platform in Russia. As a result, we predict Diener’s SWB scale with the state-of-the-art quality, introduce the first predictive models for WHO-5, with similar quality, and reach high accuracy in the prediction of clinically meaningful classes of the latter scale. Moreover, our feature analysis sheds light on the interrelated nature of the two studied scales: they are both characterized by negative sentiment expressed in text messages and by phone application usage in the morning hours, confirming some previous findings on subjective well-being manifestations. At the same time, SWB measured by Diener’s scale is reflected mostly in lexical features referring to social and affective interactions, while mental well-being is characterized by objective features that reflect physiological functioning, circadian rhythms and somatic conditions, thus saliently demonstrating the underlying theoretical differences between the two scales.
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Regular Article
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URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8978494/
https://doi.org/10.1140/epjds/s13688-022-00333-x
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LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis
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In: https://hal.archives-ouvertes.fr/hal-03294371 ; 2021 (2021)
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UPV at CheckThat! 2021: Mitigating Cultural Differences for Identifying Multilingual Check-worthy Claims ...
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Categorizing Misogynistic Behaviours in Italian, English and Spanish Tweets ; Categorización de comportamientos misóginos en tweets en italiano, inglés y español
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Masking and BERT-based Models for Stereotype Identification ; Modelos Basados en Enmascaramiento y en BERT para la Identificación de Estereotipos
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The impact of emotional signals on credibility assessment
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In: J Assoc Inf Sci Technol (2021)
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On the Detection of False Information: From Rumors to Fake News
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Dependency Syntax in the Automatic Detection of Irony and Stance
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Multilingual Irony Detection with Dependency Syntax and Neural Models
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In: Proceedings of the 28th International Conference on Computational Linguistics ; 28th International Conference on Computational Linguistics (COLING 2020) ; https://hal.archives-ouvertes.fr/hal-03102480 ; 28th International Conference on Computational Linguistics (COLING 2020), Dec 2020, Barcelona (Online), Spain. pp.1346-1358 ; https://www.aclweb.org/anthology/2020.coling-main.116/ (2020)
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Irony Detection in a Multilingual Context
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In: ECIR ; https://hal.archives-ouvertes.fr/hal-02889008 ; ECIR, Apr 2020, online, Portugal (2020)
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LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis ...
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Classifier Combination Approach for Question Classification for Bengali Question Answering System ...
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Multilingual Irony Detection with Dependency Syntax and Neural Models ...
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Multilingual Irony Detection with Dependency Syntax and Neural Models ...
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The Role of Personality and Linguistic Patterns in Discriminating Between Fake News Spreaders and Fact Checkers
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In: Natural Language Processing and Information Systems (2020)
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Do Linguistic Features Help Deep Learning? The Case of Aggressiveness in Mexican Tweets
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