Identifying Depressive Disorder in the Twitter Population

Goonmeet Bajaj; Amir Hossein Yazdavar; Krishnaprasad Thirunarayan; Amit Sheth

Identifying Depressive Disorder in the Twitter Population

Goonmeet Bajaj, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth

Wright State University

Research output: Contribution to journal › Article › peer-review

Abstract

<p> Depression is a highly prevalent public health challenge and a major cause of disability across the globe. <ul> <li> Annually 6.7% of Americans (that is, more than 16 million). </li> <li> Traditional approaches to curb depression involve survey·based methods via phone or online questionnaires. </li> <li> Large temporal gaps and cognitive bias. </li> </ul></p><p> Social media provides a method for learning users' feelings, emotions, behaviors, and decisions in real-time.</p>

Original language	American English
Journal	Default journal
State	Published - Jan 1 2017

Disciplines

Bioinformatics
Communication
Communication Technology and New Media
Computer Sciences
Databases and Information Systems
Life Sciences
OS and Networks
Physical Sciences and Mathematics
Science and Technology Studies
Social and Behavioral Sciences

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Identifying Depressive Disorder in the Twitter PopulationFinal published version, 373 KBLicense: Unspecified

Cite this

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title = "Identifying Depressive Disorder in the Twitter Population",

abstract = " Depression is a highly prevalent public health challenge and a major cause of disability across the globe. Annually 6.7% of Americans (that is, more than 16 million). Traditional approaches to curb depression involve survey·based methods via phone or online questionnaires. Large temporal gaps and cognitive bias. Social media provides a method for learning users' feelings, emotions, behaviors, and decisions in real-time.",

author = "Goonmeet Bajaj and Yazdavar, {Amir Hossein} and Krishnaprasad Thirunarayan and Amit Sheth",

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T1 - Identifying Depressive Disorder in the Twitter Population

AU - Bajaj, Goonmeet

AU - Yazdavar, Amir Hossein

AU - Thirunarayan, Krishnaprasad

AU - Sheth, Amit

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Depression is a highly prevalent public health challenge and a major cause of disability across the globe. Annually 6.7% of Americans (that is, more than 16 million). Traditional approaches to curb depression involve survey·based methods via phone or online questionnaires. Large temporal gaps and cognitive bias. Social media provides a method for learning users' feelings, emotions, behaviors, and decisions in real-time.

AB - Depression is a highly prevalent public health challenge and a major cause of disability across the globe. Annually 6.7% of Americans (that is, more than 16 million). Traditional approaches to curb depression involve survey·based methods via phone or online questionnaires. Large temporal gaps and cognitive bias. Social media provides a method for learning users' feelings, emotions, behaviors, and decisions in real-time.

UR - https://corescholar.libraries.wright.edu/knoesis/1140

M3 - Article

JO - Default journal

JF - Default journal

ER -

Identifying Depressive Disorder in the Twitter Population

Abstract

Disciplines

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