Computing Attitude and Affect in Text: Theory and Applications

Name: Computing Attitude and Affect in Text: Theory and Applications
Brand: Springer
SKU: 9789400792579
Price: 59739 HUF
Availability: InStock

Szerző: JAMES G. SHANAHAN

Nyelv:

Kötés: Puha kötésű

Kiadó: Springer

Elérhetőség: Beszállítói készleten

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Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused...

Információk a könyvről

Szerző

JAMES G. SHANAHAN

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2014

oldal

341

EAN

9789400792579

ISBN

9789400792579

Enbook ID

09070532

Kiadó

Springer

Súly

551

Méretek

155 x 19 x 20

Teljes leírás

Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the factual aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author s reports from reports of other people s opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an NLP -complete problem.

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Computing Attitude and Affect in Text: Theory and Applications

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