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Towards Automatically Classifying Depressive Symptoms from Twitter Data for Population Health
Danielle L. Mowery
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Albert Park
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Craig Bryan
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Mike Conway
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Paper Details:
Month: December
Year: 2016
Location: Osaka, Japan
Venue:
WS |
Citations
URL
SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions
Arman Cohan
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Bart Desmet
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Andrew Yates
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Luca Soldaini
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Sean MacAvaney
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Nazli Goharian
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Depression and Self-Harm Risk Assessment in Online Forums
Andrew Yates
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Arman Cohan
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Nazli Goharian
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Residualized Factor Adaptation for Community Social Media Prediction Tasks
Mohammadzaman Zamani
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H. Andrew Schwartz
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Veronica Lynn
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Salvatore Giorgi
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Niranjan Balasubramanian
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Detecting and Explaining Crisis
Rohan Kshirsagar
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Robert Morris
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Samuel Bowman
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Analysing the Causes of Depressed Mood from Depression Vulnerable Individuals
Noor Fazilla Abd Yusof
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Chenghua Lin
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Frank Guerin
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Detecting Diabetes Risk from Social Media Activity
Dane Bell
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Egoitz Laparra
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Aditya Kousik
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Terron Ishihara
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Mihai Surdeanu
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Stephen Kobourov
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http://liwc.wpengine.com/
http://www.cs.cmu.edu/
http://wwbp.org/lexica.html
http://mpqa.cs.pitt.edu/lexicons/subj_lexicon/
http://scikit-learn.org/
https://dev.twitter.com/overview/documentation
http://www.cdc.gov/brfss/
http://www.nimh.nih.gov/health/publications/depression-what-you-need-to-know-12-2015/depression-
https://www.nimh.nih.gov/health/topics/depression/index.shtml
https://www.cdc.gov/nchs/products/databriefs/db07.htm
Field Of Study
Linguistic Trends
Syntax
Task
Tagging
Question Answering
Biomedical
Language
English
Dataset
Social Media
Twitter
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