Reuters Tracer: A Large Scale System of Detecting & Verifying Real-Time News Events from Twitter

被引：35

作者：

Liu, Xiaomo ^{[1
]}

Li, Quanzhi ^{[1
]}

Nourbakhsh, Armineh ^{[1
]}

Fang, Rui ^{[1
]}

Thomas, Merine ^{[1
]}

Anderson, Kajsa ^{[1
]}

Kociuba, Russ ^{[1
]}

Vedder, Mark ^{[1
]}

Pomerville, Steve ^{[1
]}

Wudali, Ramdev ^{[1
]}

Martin, Robert ^{[1
]}

Duprey, John ^{[1
]}

Vachher, Arun ^{[1
]}

Keenan, William ^{[1
]}

Shah, Sameena ^{[1
]}

机构：

[1] Thomson Reuters, Res & Dev, Philadelphia, PA 19130 USA

来源：

CIKM'16: PROCEEDINGS OF THE 2016 ACM CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT | 2016年

关键词：

Twitter; Noise Filtering; Event Detection & Verification;

D O I：

10.1145/2983323.2983363

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

News professionals are facing the challenge of discovering news from more diverse and unreliable information in the age of social media. More and more news events break on social media first and are picked up by news media subsequently. The recent Brussels attack is such an example. At Reuters, a global news agency, we have observed the necessity of providing a more effective tool that can help our journalists to quickly discover news on social media, verify them and then inform the public. In this paper, we describe Reuters Tracer, a system for sifting through all noise to detect news events on Twitter and assessing their veracity. We disclose the architecture of our system and discuss the various design strategies that facilitate the implementation of machine learning models for noise filtering and event detection. These techniques have been implemented at large scale and successfully discovered breaking news faster than traditional journalism.

引用

页码：207 / 216

页数：10

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