Credibility filter spots hoaxes as they spread

• Autores: Hal Hodson
• Localización: New scientist, ISSN 0262-4079, Nº. 3024, 2015, pág. 19
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Now tools are arriving to help people know what's credible and what's not. CREDBANK,a database compiled by computer scientists at the Georgia Institute of Technology in Atlanta, is one. It couples crowdsourcing with machine learning to filter and study the social networks. Researchers Tanushree Mitra and Eric Gilbert started by scraping up just 1 percent of the tweets in Twitter's entire feed. Their software filtered and trimmed the tweets for spam before automatically sorting them into topics. The tweets were then sent to human workers on crowdsourcing site Mechanical Turk to confirm the topics and rate the messages on scales of certainty and accuracy. The sorting takes place right after an event unfolds on Twitter, taking just a few hours. Over 96 days in 2014, the system assessed 60 million tweets about 1,000 news events