Sentiment Analysis for PTSD Signals (Record no. 53850)

000 -LEADER
fixed length control field 04279nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-1-4614-3097-1
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421111201.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 131024s2013 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781461430971
-- 978-1-4614-3097-1
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Kagan, Vadim.
245 10 - TITLE STATEMENT
Title Sentiment Analysis for PTSD Signals
300 ## - PHYSICAL DESCRIPTION
Number of Pages X, 81 p. 23 illus., 14 illus. in color.
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Computer Science,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Introduction to PTSD Signals -- Data Source -- Text Analytics -- Scoring Engine -- System Overview -- Conclusions.
520 ## - SUMMARY, ETC.
Summary, etc 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. 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. Finally, we describe a user test conducted with users recruited from the Veteran population and present the results of the analyses on the data.
700 1# - AUTHOR 2
Author 2 Rossini, Edward.
700 1# - AUTHOR 2
Author 2 Sapounas, Demetrios.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4614-3097-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- New York, NY :
-- Springer New York :
-- Imprint: Springer,
-- 2013.
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-- text
-- txt
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-- computer
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-- rdamedia
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-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Database management.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Psychology.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Database Management.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Psychology, general.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-5768
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-- ZDB-2-SCS

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