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Sentiment Analysis for Ptsd Signals (Springerbriefs in Computer Science)

Sentiment Analysis for Ptsd Signals (Springerbriefs in Computer Science) Cover

 

Synopses & Reviews

Publisher Comments:

This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability. The use of sentiment extraction technologies allows automatic in-depth analysis of opinions and emotions expressed by individuals in their online posts. By training these automated systems with input from academic and clinical experts, the systems can be refined so that the accuracy of their detection of possible PTSD signals is comparable to that of psychologists reading the same online posts. While a portion of the literature on this and related topics explores the correlation between text patterns in archived documents and PTSD, no literature to date describes a system performing real-time analysis. Our system allows analysts to quickly identify, review, and validate online posts which have been flagged as exhibiting signs or symptoms of PTSD and enables follow-up, thus allowing for the presentation of treatment options to the authors of those posts. We describe the ontology of PTSD-related terms (i.e., terms which signal PTSD and related conditions) that need to be tracked, the algorithms used for extraction of the intensity of these signals, and the training process used to fine-tune sentiment analysis algorithms. We then present the results of processing a validation data set, different from the training set, comparing the algorithmic output with opinions of clinical psychologists, and explain how the concept can be extended to detect signals of other psychological conditions. Finally, we present a sample system architecture and implementation which can be used to engage users and their families, either anonymously or eponymously, and use the sentiment extraction algorithms as an early screening tool to alert clinicians to participants who may require close monitoring or follow-up.

Product Details

ISBN:
9781461430964
Publisher:
Springer
Subject:
Artificial Intelligence
Author:
Rossini, Edward
Author:
Kagan, Vadim
Author:
Sapounas, Demetrios
Subject:
Computational linguistics
Subject:
PTSD
Subject:
Post-traumatic stress disorder
Subject:
Psychological Signals
Subject:
Real-Time Analysis
Subject:
sentiment analysis
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Database management
Subject:
Psychology : General
Copyright:
Edition Description:
2012
Series:
SpringerBriefs in Computer Science
Publication Date:
20120315
Binding:
TRADE PAPER
Language:
English
Pages:
100

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Database » Design
Computers and Internet » Software Engineering » Software Management
Health and Self-Help » Psychology » General
Health and Self-Help » Psychology » Post-Traumatic Stress Disorder
Reference » Science Reference » Technology

Sentiment Analysis for Ptsd Signals (Springerbriefs in Computer Science)
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