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SBCS: SENTIMENT ANALYSIS FOR PTSD SIGNALS

Medical Science & Research

Health, Medicine & Nursing

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B2B & B2C

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.

Sentiment Analysis for PTSD Signals

POST SECONDARY FOUR YEAR

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Front Cover.
Other Frontmatter.
Title Page.
Copyright Page.
Acknowledgments.
Abbreviations.
Contents.
1: Introduction.
2: Introduction to PTSD Signals.
3: Data Sources.
4: Text Analytics.
5: Scoring Engine.
6: System Overview.
7: Conclusions.

Sentiment Analysis for PTSD Signals.css-1p8rvzy{position:absolute;padding-left:8px;}

Sentiment Analysis for PTSD Signals