Open AccessJournal Article
A Comprehensive Study on Social Network Mental Disorders Detection Via Online Social Media Mining
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This paper aims to review some papers regarding research in sentiment analysis on Twitter, describing the methodologies adopted and models applied, along with describing a generalized Python based approach.Abstract:
Social Network Mental Disorder Detection” or “SNMD” is an approach to analyse data and retrieve sentiment\nthat it embodies. Twitter SNMD analysis is an application of sentiment analysis on data from Twitter\n(tweets), in order to extract sentiments conveyed by the user. In this paper, we aim to review some papers\nregarding research in sentiment analysis on Twitter, describing the methodologies adopted and models\napplied, along with describing a generalized Python based approach. A prototype system is developed and\ntested.read more
Citations
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Using Social Media for Mental Health Surveillance: A Review
Ruba Skaik,Diana Inkpen +1 more
TL;DR: Big data research of social media data may also support standard surveillance approaches and provide decision-makers with usable information about users' habits and activities.
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Application of Machine Learning Methods in Mental Health Detection: A Systematic Review
Rohizah Abd Rahman,Khairuddin Omar,Shahrul Azman Mohd Noah,Mohd Shahrul Nizam Mohd Danuri,Mohammed Ali Al-Garadi +4 more
TL;DR: The presented method is an alternative approach to the early detection of mental health problems rather than using traditional strategies, such as collecting data through questionnaires or devices and sensors, which are time-consuming and costly.
Proceedings ArticleDOI
Using textual data for Personality Prediction:A Machine Learning Approach
Aditi V. Kunte,Suja S. Panicker +1 more
TL;DR: Predicting personality with the help of data through social media is a promising approach as this method does not require any questionnaires to be filled by users thus reducing time and increasing credibility.
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Emotion Sensing for Mobile Computing
Jiayu Shu,Mang Tik Chiu,Pan Hui +2 more
TL;DR: How mobile and wearable devices work as "emotion sensors" by leveraging their sensing, computing, and communication capabilities, which help monitor people's mental health, facilitate social interactions, and improve user experience is introduced.
Journal ArticleDOI
A survey on mental health detection in Online Social Network
TL;DR: Major findings revealed that the most frequently used method in mental health detection is machine learning techniques, with Support Vector Machine (SVM) as the most chosen algorithm and Twitter is the major data source from OSN with English language used formental health detection.
References
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Journal ArticleDOI
Using Social Media for Mental Health Surveillance: A Review
Ruba Skaik,Diana Inkpen +1 more
TL;DR: Big data research of social media data may also support standard surveillance approaches and provide decision-makers with usable information about users' habits and activities.
Journal ArticleDOI
Application of Machine Learning Methods in Mental Health Detection: A Systematic Review
Rohizah Abd Rahman,Khairuddin Omar,Shahrul Azman Mohd Noah,Mohd Shahrul Nizam Mohd Danuri,Mohammed Ali Al-Garadi +4 more
TL;DR: The presented method is an alternative approach to the early detection of mental health problems rather than using traditional strategies, such as collecting data through questionnaires or devices and sensors, which are time-consuming and costly.
Proceedings ArticleDOI
Using textual data for Personality Prediction:A Machine Learning Approach
Aditi V. Kunte,Suja S. Panicker +1 more
TL;DR: Predicting personality with the help of data through social media is a promising approach as this method does not require any questionnaires to be filled by users thus reducing time and increasing credibility.
Journal ArticleDOI
Emotion Sensing for Mobile Computing
Jiayu Shu,Mang Tik Chiu,Pan Hui +2 more
TL;DR: How mobile and wearable devices work as "emotion sensors" by leveraging their sensing, computing, and communication capabilities, which help monitor people's mental health, facilitate social interactions, and improve user experience is introduced.
Journal ArticleDOI
A survey on mental health detection in Online Social Network
TL;DR: Major findings revealed that the most frequently used method in mental health detection is machine learning techniques, with Support Vector Machine (SVM) as the most chosen algorithm and Twitter is the major data source from OSN with English language used formental health detection.