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Predicting Attitude and Actions of Twitter Users

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.

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Cited By

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  • (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
  • (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
  • (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
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    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
    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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    Publication History

    Published: 07 March 2016

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    Author Tags

    1. attitude
    2. brand
    3. social media
    4. twitter

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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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    Cited By

    View all
    • (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
    • (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
    • (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
    • (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
    • (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
    • (2019)Tackling challenges of neural purchase stage identification from imbalanced twitter dataNatural Language Engineering10.1017/S1351324919000433(1-29)Online publication date: 15-Aug-2019
    • (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
    • (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
    • (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
    • (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
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