Social media data mining and analytics (Record no. 230027)

MARC details
000 -LEADER
fixed length control field 02109nam a22002417a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250714184002.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240305b ||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781118824856
040 ## - CATALOGING SOURCE
Transcribing agency AL
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 070.4
Item number SZAS
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Gabor Szabo
9 (RLIN) 152836
245 ## - TITLE STATEMENT
Title Social media data mining and analytics
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New Jersey
Name of publisher, distributor, etc. John Wiley & Sons
Date of publication, distribution, etc. 2019
300 ## - PHYSICAL DESCRIPTION
Extent xxxv,316p.
Other physical details PB
Dimensions 23x18.5cm
365 ## - TRADE PRICE
Source of price type code General
Price type code 7739
Price amount ₹2916.14
Currency code ₹
Unit of pricing ₹3888.00
Price note 25%
Price effective from 15-02-2024
520 ## - SUMMARY, ETC.
Summary, etc. Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization<br/>How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions<br/>How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Source of heading or term Social Media
Topical term or geographic name entry element Journalism
9 (RLIN) 152837
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Polatkan, Gungor;et
9 (RLIN) 152838
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Boykin, Oscar
9 (RLIN) 218704
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Chalkiopoulos, Antonios
9 (RLIN) 218705
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     MAJMC St Aloysius PG Library St Aloysius PG Library 02/22/2024 Biblios Book Point 2916.14   070.4 SZAS PG024632 03/05/2024 3888.00 03/05/2024 Book