research-article

GOP primary season on twitter: "popular" political sentiment in social media

Authors:

Padmini Srinivasan,

Bob BoyntonAuthors Info & Claims

WSDM '13: Proceedings of the sixth ACM international conference on Web search and data mining

Pages 517 - 526

https://doi.org/10.1145/2433396.2433463

Published: 04 February 2013 Publication History

Abstract

As mainstream news media and political campaigns start to pay attention to the political discourse online, a systematic analysis of political speech in social media becomes more critical. What exactly do people say on these sites, and how useful is this data in estimating political popularity? In this study we examine Twitter discussions surrounding seven US Republican politicians who were running for the US Presidential nomination in 2011. We show this largely negative rhetoric to be laced with sarcasm and humor and dominated by a small portion of users. Furthermore, we show that using out-of-the-box classification tools results in a poor performance, and instead develop a highly optimized multi-stage approach designed for general-purpose political sentiment classification. Finally, we compare the change in sentiment detected in our dataset before and after 19 Republican debates, concluding that, at least in this case, the Twitter political chatter is not indicative of national political polls.

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Cited By

Mejova YAn JMorales GKwak H(2022)Modeling Political Activism around Gun Debate via Social MediaACM Transactions on Social Computing10.1145/35321025:1-4(1-28)Online publication date: 26-Nov-2022
https://dl.acm.org/doi/10.1145/3532102
Fu YLiu Y(2022)Contrastive transformer based domain adaptation for multi-source cross-domain sentiment classificationKnowledge-Based Systems10.1016/j.knosys.2022.108649245(108649)Online publication date: Jun-2022
https://doi.org/10.1016/j.knosys.2022.108649
Coppola FGrimaldi MFasolino I(2022)Constructing Dynamic Scenarios of Crime Risk Exposure. A Methodological Proposal Based on Geo-Social Media DataGeomatics for Green and Digital Transition10.1007/978-3-031-17439-1_11(156-165)Online publication date: 8-Oct-2022
https://doi.org/10.1007/978-3-031-17439-1_11
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Index Terms

GOP primary season on twitter: "popular" political sentiment in social media
1. Information systems
  1. Information retrieval
  2. Information storage systems

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Published In

cover image ACM Conferences

WSDM '13: Proceedings of the sixth ACM international conference on Web search and data mining

February 2013

816 pages

ISBN:9781450318693

DOI:10.1145/2433396

General Chairs:
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy
,
Program Chairs:
Paolo Ferragina
University of Pisa, Italy
,
Aristides Gionis
Yahoo! Research, Barcelona, Spain

Copyright © 2013 ACM.

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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Published: 04 February 2013

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WSDM 2013: Sixth ACM International Conference on Web Search and Data Mining

February 4 - 8, 2013

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Cited By

Mejova YAn JMorales GKwak H(2022)Modeling Political Activism around Gun Debate via Social MediaACM Transactions on Social Computing10.1145/35321025:1-4(1-28)Online publication date: 26-Nov-2022
https://dl.acm.org/doi/10.1145/3532102
Fu YLiu Y(2022)Contrastive transformer based domain adaptation for multi-source cross-domain sentiment classificationKnowledge-Based Systems10.1016/j.knosys.2022.108649245(108649)Online publication date: Jun-2022
https://doi.org/10.1016/j.knosys.2022.108649
Coppola FGrimaldi MFasolino I(2022)Constructing Dynamic Scenarios of Crime Risk Exposure. A Methodological Proposal Based on Geo-Social Media DataGeomatics for Green and Digital Transition10.1007/978-3-031-17439-1_11(156-165)Online publication date: 8-Oct-2022
https://doi.org/10.1007/978-3-031-17439-1_11
Gagliardi GGregori LSuozzi A(2021)L’impatto emotivo della comunicazione istituzionale durante la pandemia di Covid-19: uno studio di Twitter Sentiment AnalysisProceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 202010.4000/books.aaccademia.8575(205-210)Online publication date: 3-Sep-2021
https://doi.org/10.4000/books.aaccademia.8575
Cortis KDavis B(2021)Over a decade of social opinion mining: a systematic reviewArtificial Intelligence Review10.1007/s10462-021-10030-254:7(4873-4965)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1007/s10462-021-10030-2
Castellanos EXie HBrenner P(2021)Global News Sentiment AnalysisProceedings of the 2019 International Conference of The Computational Social Science Society of the Americas10.1007/978-3-030-77517-9_9(121-139)Online publication date: 3-Oct-2021
https://doi.org/10.1007/978-3-030-77517-9_9
Skoric MLiu JJaidka K(2020)Electoral and Public Opinion Forecasts with Social Media Data: A Meta-AnalysisInformation10.3390/info1104018711:4(187)Online publication date: 31-Mar-2020
https://doi.org/10.3390/info11040187
Haq EBraud TKwon YHui P(2020)A Survey on Computational PoliticsIEEE Access10.1109/ACCESS.2020.30349838(197379-197406)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3034983
Lim WHo CTing C(2020)Sentiment Analysis by Fusing Text and Location Features of Geo-Tagged TweetsIEEE Access10.1109/ACCESS.2020.30278458(181014-181027)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3027845
Cardon D(2020)What Are Digital Reputation Measures Worth?The Performance Complex10.1093/oso/9780198861669.003.0010(208-227)Online publication date: 20-Aug-2020
https://doi.org/10.1093/oso/9780198861669.003.0010
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