Sentiment Analysis for PTSD Signals by Vadim Kagan Edward Rossini & Demetrios Sapounas

Author:Vadim Kagan, Edward Rossini & Demetrios Sapounas
Language: eng
Format: epub
Publisher: Springer New York, New York, NY

Opinion mining, as the name implies, concentrates on opinions—thought-out conclusions that are, nevertheless, still open for discussion. Opinions are often classified into subclasses, for example: views are usually more subjective; beliefs imply conscious acceptance; convictions are strongly held beliefs; and persuasions typically indicate beliefs that are based on assurance of their truth.

Sentiment analysis in its pure form does not attempt to judge objectivity or the strength of the factual base, but rather measures the intensity and polarity of the feelings expressed towards the topic of interest. Because of that, it is best suited for measurement of emotions expressed in the textual documents.There are several approaches to calculating sentiment analysis scores, each with its strengths and weaknesses. They differ in the models used—from purely statistical to pure natural language processing (NLP)-based to hybrids—as well as in the sensitivity (calculating overall sentiment of entire documents versus calculating sentiment toward particular topic), and granularity (ranging from simple positive/negative to large, potentially infinite, number of levels between extremely negative and extremely positive). Such differences manifest themselves externally not only in the results produced, but also in the resources required for calculations and in speed of processing. Most of the commercially available systems make one sort of tradeoff or another, making them better suitable for a particular market segment.

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