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The Resource A Practical Guide to Sentiment Analysis, edited by Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, Antonio Feraco, (electronic resource)

A Practical Guide to Sentiment Analysis, edited by Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, Antonio Feraco, (electronic resource)

Label
A Practical Guide to Sentiment Analysis
Title
A Practical Guide to Sentiment Analysis
Statement of responsibility
edited by Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, Antonio Feraco
Contributor
Editor
Subject
Language
eng
Summary
This edited work presents studies and discussions that clarify the challenges and opportunities of sentiment analysis research. While sentiment analysis research has become very popular in the past ten years, most companies and researchers still approach it simply as a polarity detection problem. In reality, sentiment analysis is a {u2018}suitcase problem{u2019} that requires tackling many natural language processing subtasks, including microtext analysis, sarcasm detection, anaphora resolution, subjectivity detection and aspect extraction. In this book, the authors propose an overview of the main issues and challenges associated with current sentiment analysis research and provide some insights on practical tools and techniques that can be exploited to both advance the state of the art in all sentiment analysis subtasks and explore new areas in the same context. Readers will discover sentiment mining techniques that can be exploited for the creation and automated upkeep of review and opinion aggregation websites, in which opinionated text and videos are continuously gathered from the Web and not restricted to just product reviews, but also to wider topics such as political issues and brand perception. The book also enables researchers to see how affective computing and sentiment analysis have a great potential as a sub-component technology for other systems. They can enhance the capabilities of customer relationship management and recommendation systems allowing, for example, to find out which features customers are particularly happy about or to exclude from the recommendations items that have received very negative feedbacks. Similarly, they can be exploited for affective tutoring and affective entertainment or for troll filtering and spam detection in online social communication
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Is part of
Image bit depth
0
Literary form
non fiction
Series statement
Socio-Affective Computing,
Series volume
5
A Practical Guide to Sentiment Analysis, edited by Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, Antonio Feraco, (electronic resource)
Label
A Practical Guide to Sentiment Analysis, edited by Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, Antonio Feraco, (electronic resource)
Link
http://libproxy.rpi.edu/login?url=http://dx.doi.org/10.1007/978-3-319-55394-8
Publication
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Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Preface -- Affective Computing and Sentiment Analysis -- Many Facets of Sentiment Analysis -- Reflections on Sentiment/Opinion Analysis -- Challenges in Sentiment Analysis -- Sentiment Resources: Lexicons and Datasets -- Generative Models for Sentiment Analysis and Opinion Mining -- Social Media Summarization -- Deception Detection and Opinion Spam -- Concept-Level Sentiment Analysis with SenticNet -- Index
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9783319553948&userID=ebsco-test&password=ebsco-test
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unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b4258178'}
Extent
VII, 196 p. 16 illus., 7 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783319553948
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote

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