Breaking News Detection and Tracking in Twitter
Abstract
Twitter has been used as one of the communication channels for spreading breaking news. We propose a method to collect, group, rank and track breaking news in Twitter. Since short length messages make similarity comparison difficult, we boost scores on proper nouns to improve the grouping results. Each group is ranked based on popularity and reliability factors. Current detection method is limited to facts part of messages. We developed an application called “Hotstream” based on the proposed method. Users can discover breaking news from the Twitter timeline. Each story is provided with the information of message originator, story development and activity chart. This provides a convenient way for people to follow breaking news and stay informed with real-time updates.
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Social media platforms are increasingly used to gather information about societal issues and breaking news developments.
“Social media platforms are increasingly being used as a tool for gathering information about, for example, societal issues (Lazer et al. 2009), and to find out about the latest developments during breaking news stories (Phuvipadawat and Murata 2010).”
From Detection and Resolution of Rumours in Social Media (2019) · cites this paper as Phuvipadawat and Murata 2010
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Processing Social Media Messages in Mass Emergency: A Survey
Imran, M., Castillo, C., Diaz, F., & Vieweg, S. (2015) · ACM Computing Surveys · doi:10.1145/2771588 · Cited by 804 · see citing works
Detection and Resolution of Rumours in Social Media
Zubiaga, A., Aker, A., Bontcheva, K., Liakata, M., & Procter, R. (2019) · ACM Computing Surveys · doi:10.1145/3161603 · Cited by 608 · see citing works
“Social media platforms are increasingly being used as a tool for gathering information about, for example, societal issues [Lazer et al. 2009] and to find out about the latest developments during breaking news stories [Phuvipadawat and Murata 2010].”
MethodLampropoulos, G., Ferdig, R. E., & Kaplan-Rakowski, R. (2023) · doi:10.2139/ssrn.4468181 · Cited by 33 · see citing works
- Authors
- Phuvipadawat, S., & Murata, T.
- Affiliations
- Tokyo Institute of Technology (JP)
- ORCID
- Murata, Tsuyoshi
- Venue
- 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology
- Publisher
- IEEE
- Published
- 2010-08
- Pages
- 120-123
- OpenAlex
- W2046210419
- Cited by
- 275
- References
- 0
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 3 · 2023: 10 · 2022: 19 · 2021: 17 · 2020: 17 · 2019: 33 · 2018: 29 · 2017: 34 · 2016: 32 · 2015: 29 · 2014: 18 · 2013: 14 · 2012: 9
- FWCI
- 25.24
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (publishedVersion)
- Tokyo Tech Research Repository (Tokyo Institute of Technology) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Public Relations and Crisis Communication
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Keywords
- news tracking, Twitter, news ranking, news popularity, news reliability, short text similarity
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