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Sentiment Analysis in Social Networks / (Record no. 21233)

MARC details
000 -LEADER
fixed length control field	03017nam a2200265 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number	9780128044124
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number	9780128044384
040 ## - CATALOGING SOURCE
Original cataloging agency	UTB
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name	Pozzi, Federico Alberto.
Relator term	author.
245 10 - TITLE STATEMENT
Title	Sentiment Analysis in Social Networks /
Statement of responsibility, etc.	Federico Alberto Pozzi, Elisabetta Fersini, Enza Messina, Bing Liu.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc.	Cambridge, MA :
Name of publisher, distributor, etc.	Morgan Kaufmann,
Date of publication, distribution, etc.	2017.
500 ## - GENERAL NOTE
General note	This book is automatically accessible within the University internet network. To learn how to access it outside the campus, visit: https://www.utb.edu.bn/media/cv5fcgwb/remote-access-for-ebscohost.pdf
520 ## - SUMMARY, ETC.
Summary, etc.	The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network mining Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element	Social networks
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element	Natural language processing (Computer science)
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element	Computational linguistics
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term	author.
Personal name	Fersini, Elisabetta.
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term	author
Personal name	Messina, Enza.
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term	author.
Personal name	Bing Liu
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier	<a href="https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1144691&site=ehost-live">https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1144691&site=ehost-live</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme	Local Classification
Koha item type	Ebook Collection
998 ## - LOCAL CONTROL INFORMATION (RLIN)
Internal field	Electronic book
CC (RLIN)	Reference No: 4736965 / 10.12.21 / ns277138 Date: 12 October 2021 -- (UTB) – EBSCO International, INC

Holdings
Withdrawn status	Lost status	Source of classification or shelving scheme	Damaged status	Not for loan	Home library	Current library	Date acquired	Total Checkouts	Date last seen	Uniform Resource Identifier	Price effective from	Koha item type	Public note
		Local Classification	Not damaged		Universiti Teknologi Brunei Library	Universiti Teknologi Brunei Library	12/10/2021		30/12/2023	https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1144691&site=ehost-live	12/10/2021	Ebook Collection	This book is automatically accessible within the University internet network. To learn how to access it outside the campus, visit: https://www.utb.edu.bn/media/cv5fcgwb/remote-access-for-ebscohost.pdf