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Our sentiments, exactly

Published: 01 April 2009 Publication History

Abstract

With sentiment analysis algorithms, companies can identify and assess the wide variety of opinions found online and create computational models of human opinion.

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  • (2023)Classification of Tweets Into Facts and Opinions Using Recurrent Neural NetworksInternational Journal of Technology and Human Interaction10.4018/IJTHI.31935819:1(1-14)Online publication date: 10-Mar-2023
  • (2022)Decoding customer experiences in rail transport service: application of hybrid sentiment analysisPublic Transport10.1007/s12469-021-00289-715:1(31-60)Online publication date: 22-Feb-2022
  • (2021)Türkçe Metinlerde Duygu AnaliziJournal of Yaşar University10.19168/jyasar.92884316:63(1516-1536)Online publication date: 30-Sep-2021
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Published In

cover image Communications of the ACM
Communications of the ACM  Volume 52, Issue 4
A Direct Path to Dependable Software
April 2009
134 pages
ISSN:0001-0782
EISSN:1557-7317
DOI:10.1145/1498765
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 2009
Published in CACM Volume 52, Issue 4

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Cited By

View all
  • (2023)Classification of Tweets Into Facts and Opinions Using Recurrent Neural NetworksInternational Journal of Technology and Human Interaction10.4018/IJTHI.31935819:1(1-14)Online publication date: 10-Mar-2023
  • (2022)Decoding customer experiences in rail transport service: application of hybrid sentiment analysisPublic Transport10.1007/s12469-021-00289-715:1(31-60)Online publication date: 22-Feb-2022
  • (2021)Türkçe Metinlerde Duygu AnaliziJournal of Yaşar University10.19168/jyasar.92884316:63(1516-1536)Online publication date: 30-Sep-2021
  • (2018)Die Herausforderungen der automatisierten Textanalyse im Wandel der ZeitInformationswissenschaft10.7767/boehlau.9783205791935.291(291-302)Online publication date: 4-Jul-2018
  • (2018)Classifying facts and opinions in Twitter messages: a deep learning-based approachJournal of Business Analytics10.1080/2573234X.2018.15066871:1(29-39)Online publication date: 23-Aug-2018
  • (2017)Kundenbindung durch KundenbegeisterungHandbuch Kundenbindungsmanagement10.1007/978-3-658-13650-5_11(273-298)Online publication date: 19-Feb-2017
  • (2016)New Digital Metrics in Marketing: A Comparative Study on Social Media UseMedia and Metamedia Management10.1007/978-3-319-46068-0_45(343-350)Online publication date: 24-Nov-2016
  • (2015)A sales forecasting model for consumer products based on the influence of online word-of-mouthInformation Systems and e-Business Management10.1007/s10257-014-0265-013:3(445-473)Online publication date: 1-Aug-2015
  • (2015)Generating Product Feature Hierarchy from Product ReviewsWeb Information Systems and Technologies10.1007/978-3-319-27030-2_17(264-278)Online publication date: 16-Dec-2015
  • (2014)Uncovering customer service experiences with Twitter: the case of airline industryManagement Decision10.1108/MD-03-2012-023552:4(705-723)Online publication date: 13-May-2014
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