short-paper

Predicting Attitude and Actions of Twitter Users

Authors:

Michelle ZhouAuthors Info & Claims

IUI '16: Proceedings of the 21st International Conference on Intelligent User Interfaces

Pages 2 - 6

https://doi.org/10.1145/2856767.2856800

Published: 07 March 2016 Publication History

Abstract

In this paper, we present computational models to predict Twitter users' attitude towards a specific brand through their personal and social characteristics. We also predict their likelihood of taking different actions based on their attitudes. In order to operationalize our research on users' attitude and actions, we collected ground-truth data through surveys of Twitter users. We have conducted experiments using two real world datasets to validate the effectiveness of our attitude and action prediction framework. Finally, we show how our models can be integrated with a visual analytics system for customer intervention.

References

[1]

Gao, H. Mahmud, J., Chen, J., Nichols, J, Zhou, M.X. Modeling User Attitude Toward Controversial Topics in Online Social Media. In Proc. ICWSM 2014.

[2]

Hoyer, W.D., Maclnnis, D.J. Pieters, R. Consumer Behavior. 5th Edition, 2008.

[3]

Hu, X.; Tang, J.; Gao, H.; and Liu, H. 2013a. Unsupervised sentiment analysis with emotional signals. In Proc. of the WWW 2013, 607--618.

Digital Library

[4]

Hu, X.; Tang, L.; Tang, J.; and Liu, H. 2013b. Exploiting social relations for sentiment analysis in microblogging. In Proc. of the WSDM 2013, 537--546.

Digital Library

[5]

Jansen, B. J., Zhang, M., Sobel, K., et al. 2009. Twitter power: Tweets as electronic word of mouth. Journal of American Society for Information Science & Technology, 60(11), 2169--2188.

Digital Library

[6]

Jiang, L.; Yu, M.; Zhou, M.; Liu, X.; and Zhao, T. 2011. Target dependent twitter sentiment classification. In Proc. of the HLT '11, 151--160.

Digital Library

[7]

Kim, J.; Yoo, J.; Lim, H.; Qiu, H.; Kozareva, Z.; and Galstyan, A. 2013. Sentiment prediction using collaborative filtering. In Proc. of the ICWSM 2013.

[8]

Lee, K.; Mahmud, J.; Chen, J., Zhou, M.X., Nichols, J. 2014. Who Will Retweet This? Automatically Identifying and Engaging Strangers on Twiteer to Spread Information. In Proc. IUI 2014.

Digital Library

[9]

Li, F.; Huang, M.; and Zhu, X. 2010. Sentiment analysis with global topics and local dependency. In Proc. AAAI 2010.

Digital Library

[10]

Li, D.; Shuai, X.; Sun, G.; Tang, J.; Ding, Y.; and Luo, Z. 2012. Mining topic-level opinion influence in microblog. In Proc. CIKM 2012.

Digital Library

[11]

Lin, C., and He, Y. 2009. Joint sentiment/topic model for sentiment analysis. In Proc. CIKM 2009.

Digital Library

[12]

Pang, B. and Lee, L. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval (2).

Digital Library

[13]

Schiman, L., and Kanuk, L. 2010. Consumer Behavior, 10th edition. Prentice Hall.

[14]

Tan, C.; Lee, L.; Tang, J.; Jiang, L.; Zhou, M.; and Li, P. 2011. User-level sentiment analysis incorporating social networks. In Proc. of KDD 2011.

Digital Library

[15]

Witten, I.H., Frank, E., and Hall, M.A. 2011. Data mining: Practical machine learning tools and techniques, 3rd Edition. Morgan Kaufmann.

Digital Library

Cited By

Thakur NPatel KPoon AShah RAzizi NHan C(2023)A Comprehensive Analysis and Investigation of the Public Discourse on Twitter about Exoskeletons from 2017 to 2023Future Internet10.3390/fi1510034615:10(346)Online publication date: 22-Oct-2023
https://doi.org/10.3390/fi15100346
Zhang HKwak HGao WAn JHorvát ÁHall WContractor NFröhling LOgnayova KTaneja HWeber IGligori? KMejova Y(2023)Wearing Masks Implies Refuting Trump?: Towards Target-specific User Stance Prediction across Events in COVID-19 and US Election 2020Proceedings of the 15th ACM Web Science Conference 202310.1145/3578503.3583606(23-32)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3578503.3583606
Islam NMehboob MJaved R(2022)Analytics of User Behaviors on Twitter Using Machine LearningHandbook of Research on Artificial Intelligence Applications in Literary Works and Social Media10.4018/978-1-6684-6242-3.ch014(302-337)Online publication date: 30-Dec-2022
https://doi.org/10.4018/978-1-6684-6242-3.ch014
Show More Cited By

Index Terms

Predicting Attitude and Actions of Twitter Users
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

IUI '16: Proceedings of the 21st International Conference on Intelligent User Interfaces

March 2016

446 pages

ISBN:9781450341370

DOI:10.1145/2856767

General Chairs:
Jeffrey Nichols
Google Inc, USA
,
Jalal Mahmud
IBM Research, USA
,
John O'Donovan
UC Santa Barbara, USA
,
Program Chairs:
Cristina Conati
University of British Columbia, Canada
,
Massimo Zancanaro
Bruno Kessler Foundation, Italy

Copyright © 2016 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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New York, NY, United States

Publication History

Published: 07 March 2016

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IUI'16

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IUI'16: 21st International Conference on Intelligent User Interfaces

March 7 - 10, 2016

California, Sonoma, USA

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IUI '16 Paper Acceptance Rate 49 of 194 submissions, 25%;

Overall Acceptance Rate 746 of 2,811 submissions, 27%

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IUI '25

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30th International Conference on Intelligent User Interfaces

March 24 - 27, 2025

Cagliari , Italy

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Cited By

Thakur NPatel KPoon AShah RAzizi NHan C(2023)A Comprehensive Analysis and Investigation of the Public Discourse on Twitter about Exoskeletons from 2017 to 2023Future Internet10.3390/fi1510034615:10(346)Online publication date: 22-Oct-2023
https://doi.org/10.3390/fi15100346
Zhang HKwak HGao WAn JHorvát ÁHall WContractor NFröhling LOgnayova KTaneja HWeber IGligori? KMejova Y(2023)Wearing Masks Implies Refuting Trump?: Towards Target-specific User Stance Prediction across Events in COVID-19 and US Election 2020Proceedings of the 15th ACM Web Science Conference 202310.1145/3578503.3583606(23-32)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3578503.3583606
Islam NMehboob MJaved R(2022)Analytics of User Behaviors on Twitter Using Machine LearningHandbook of Research on Artificial Intelligence Applications in Literary Works and Social Media10.4018/978-1-6684-6242-3.ch014(302-337)Online publication date: 30-Dec-2022
https://doi.org/10.4018/978-1-6684-6242-3.ch014
Liu XHe DWu D(2020)Breaking Social Media Bubbles for Information Globalization: A Cross-Cultural and Cross-Language User-Centered Sense-Making ApproachData and Information Management10.2478/dim-2020-00204:4(297-305)Online publication date: 20-Nov-2020
https://doi.org/10.2478/dim-2020-0020
Liu SWang XCollins CDou WOuyang FEl-Assady MJiang LKeim D(2019)Bridging Text Visualization and Mining: A Task-Driven SurveyIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.283434125:7(2482-2504)Online publication date: 1-Jul-2019
https://doi.org/10.1109/TVCG.2018.2834341
Adel HChen FChen Y(2019)Tackling challenges of neural purchase stage identification from imbalanced twitter dataNatural Language Engineering10.1017/S1351324919000433(1-29)Online publication date: 15-Aug-2019
https://doi.org/10.1017/S1351324919000433
Pandey RPurohit HBein D(2018)Generic architecture of a social media-driven intervention support system for smart citiesProceedings of the Workshop Program of the 19th International Conference on Distributed Computing and Networking10.1145/3170521.3170528(1-6)Online publication date: 4-Jan-2018
https://dl.acm.org/doi/10.1145/3170521.3170528
Liu XXu ASinha VAkkiraju RMandryk RHancock MPerry MCox A(2018)Voice of CustomerExtended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3170427.3188454(1-6)Online publication date: 20-Apr-2018
https://dl.acm.org/doi/10.1145/3170427.3188454
Tyshchuk YWallace W(2018)Modeling Human Behavior on Social Media in Response to Significant EventsIEEE Transactions on Computational Social Systems10.1109/TCSS.2018.28157865:2(444-457)Online publication date: Jun-2018
https://doi.org/10.1109/TCSS.2018.2815786
Kursuncu UGaur MLokala UThirunarayan KSheth AArpinar I(2018)Predictive Analysis on Twitter: Techniques and ApplicationsEmerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining10.1007/978-3-319-94105-9_4(67-104)Online publication date: 18-Sep-2018
https://doi.org/10.1007/978-3-319-94105-9_4
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