User generated content has become a major trend in today’s journalistic ecosystem, where in many cases news arrive on social media platforms even before they reach mainstream media. Due to today’s hyperconnected society, this type of event is becoming more frequent, and “news-like” information is being produced all over the Internet on blogs, posted on Facebook or Twitter, Wikipedia, or any other platform that allows users to share their ideas and experiences. In this chapter, we describe SwarmPulse, a system that extracts news by combing through Wikipedia and Twitter to extract newsworthy items. We measured the accuracy of SwarmPulse comparing it against the Reuters and CNN RSS feeds and the Google News feed. We found precision of 83 % and recall of 15 % against these sources.
- News Item
- Twitter User
- News Channel
- Breaking News
- Match Strength
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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The reader can try out the prototype version of SwarmPulse at swarmpulse.galaxyadvisors.com.
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de Oliveira, J.M., Gloor, P.A. (2016). The Citizen IS the Journalist: Automatically Extracting News from the Swarm. In: Zylka, M., Fuehres, H., Fronzetti Colladon, A., Gloor, P. (eds) Designing Networks for Innovation and Improvisation. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-42697-6_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42696-9
Online ISBN: 978-3-319-42697-6