The DOI matches its Crossref record; 18 of the 19 references it cites were found in a registry or an index.
Sentiment analysis on tweets for social events
Abstract
Sentiment analysis or opinion mining is an important type of text analysis that aims to support decision making by extracting and analyzing opinion oriented text, identifying positive and negative opinions, and measuring how positively or negatively an entity (i.e., people, organization, event, location, product, topic, etc.) is regarded. As more and more users express their political and religious views on Twitter, tweets become valuable sources of people's opinions. Tweets data can be efficiently used to infer people's opinions for marketing or social studies. This paper proposes a Tweets Sentiment Analysis Model (TSAM) that can spot the societal interest and general people's opinions in regard to a social event. In this paper, Australian federal election 2010 event was taken as an example for sentiment analysis experiments. We are primarily interested in the sentiment of the specific political candidates, i.e., two primary minister candidates - Julia Gillard and Tony Abbot. Our experimental results demonstrate the effectiveness of the system.
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“The automation of sentiment detection on these social networks has gained attention for various purposes [18][19][20].”
From Survey on AI-Based Multimodal Methods for Emotion Detection (2019) · cites this paper as [19]
Citations
Cites
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Cited by
Sorted by citations
Alharbi, A. S. M., & de Doncker, E. (2018) · Cognitive Systems Research · doi:10.1016/j.cogsys.2018.10.001 · Cited by 228
Sentiment analysis and opinion mining on educational data: A survey
Shaik, T., Tao, X., Dann, C., Xie, H., Li, Y., & Galligan, L. (2023) · Natural Language Processing Journal · doi:10.1016/j.nlp.2022.100003 · Cited by 215
“The analysis of these sources to extract sentiment or opinions of users started a decade ago [3, 4].”
BackgroundSelf-citationMonitoring the public opinion about the vaccination topic from tweets analysis
D’Andrea, E., Ducange, P., Bechini, A., Renda, A., & Marcelloni, F. (2018) · Expert Systems with Applications · doi:10.1016/j.eswa.2018.09.009 · Cited by 169
“, 2011) and the outcome of political elections (Zhou et al., 2013).”
BackgroundSurvey on AI-Based Multimodal Methods for Emotion Detection
Marechal, C., Mikołajewski, D., Tyburek, K., Prokopowicz, P., Bougueroua, L., Ancourt, C., & Węgrzyn-Wolska, K. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-16272-6_11 · Cited by 137
Big data analytics and international negotiations: Sentiment analysis of Brexit negotiating outcomes
Georgiadou, E., Angelopoulos, S. P., & Drake, H. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.102048 · Cited by 116
Metadata
- Authors
- Zhou, X., Tao, X., Yong, J., & Yang, Z.
- Affiliations
- Queensland University of Technology (AU)
- University of Southern Queensland (AU)
- Aalborg University (DK)
- Venue
- Proceedings of the 2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
- Publisher
- IEEE
- Published
- 2013-06
- Pages
- 557-562
- OpenAlex
- W1990239322
- Cited by
- 124
- References
- 19
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 7 · 2023: 11 · 2022: 15 · 2021: 13 · 2020: 11 · 2019: 14 · 2018: 11 · 2017: 8 · 2016: 10 · 2015: 8 · 2014: 7
- FWCI
- 5.38
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Computer Supported Cooperative Work in Design (CSCWD) (publishedVersion)
- University of Southern Queensland ePrints (University of Southern Queensland) (acceptedVersion)
- VBN Forskningsportal (Aalborg Universitet) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Keywords
- sentiment analysis, Twitter, tweets, social gatherings, political attitudes, political candidates, Julia Gillard, Tony Abbott, public opinion
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