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A Comparison Among Significance Tests and Other Feature Building Methods for Sentiment Analysis: A First Study Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Reading the Author and Speaker: Towards a Holistic and Deep Approach on Automatic Assessment of What is in One’s Words

Author : Björn W. Schuller

Published in: Computational Linguistics and Intelligent Text Processing

Publisher: Springer International Publishing

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Abstract

Computational text analysis is continuously becoming richer in ways the author of a text is ‘read’ in terms of the states and traits of the person behind the words such as writer’s age, gender, personality, emotion or sentiment to name but a few. Similarly, in the analysis of spoken language, one finds a broadening palette of such characteristics of speakers automatically analysed in recent Computational Paralinguistics research. It seems wise to assess these characteristics in one pass to understand their interrelationship rather than going one by one in isolation. As an example, it may help to estimate one’s personality knowing the age, gender, and cultural background of the person. Thus, a holistic approach is advocated that aims at automatically assessing the ‘larger’ picture of a person that wrote or spoke words of analysis. Here, a short motivation and inspirations ‘en route’ to holistic author and word-based speaker profiling are given.

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previous chapter Detecting Sockpuppets in Deceptive Opinion Spam
next chapter Improving Cross-Topic Authorship Attribution: The Role of Pre-Processing
Footnotes
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More information can be accessed from http://​www.​compare.​openaudio.​eu.
 
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Metadata
Title
Reading the Author and Speaker: Towards a Holistic and Deep Approach on Automatic Assessment of What is in One’s Words
Author
Björn W. Schuller
Copyright Year
2018
Book
Computational Linguistics and Intelligent Text Processing

Print ISBN: 978-3-319-77115-1

Electronic ISBN: 978-3-319-77116-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-77116-8_20

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