Parsing the Twitterverse: New Algorithms Analyze Tweets: Scientific American
By Francie Diep, Scientific American, July 22, 2011
Researchers have been trolling Twitter for insights into the human condition since shortly after the site launched in 2006. In aggregate, the service provides a vast database of what people are doing, thinking and feeling. But the research tools at scientists’ disposal are highly imperfect. Keyword searches, for example, return many hits but offer a poor sense of overall trends.When computer scientist James H. Martin of the University of Colorado at Boulder searched for tweets about the 2010 earthquake in Haiti, he found 14 million. “You can’t hire grad students to read them all,” he says. Researchers need a more automated approach. …
For full text of the article, visit Parsing the Twitterverse: New Algorithms Analyze Tweets: Scientific American.
- Parsing the Twitterverse: New Algorithms Analyze Tweets (scientificamerican.com)
Tags: 2010 Haiti earthquake, Citizen Science, Crowdsourcing, Facebook, Online Communities, Participatory Sensing, Scientific American, Social media, Social Media, Tumblr, Twitter, University of Colorado at Boulder, VGI
Dr. Lea Shanley is the founder and former co-Chair of the Federal Community of Practice on Crowdsourcing and Citizen Science, a vibrant community of 200 federal employees from more than 35 agencies. She is also a co-founding member of the Citizen Science Association. Dr. Shanley recently served as a Presidential Innovation Fellow at NASA, where she helped to foster a culture of open innovation. Prior to this, she founded and directed the Commons Lab at the Wilson Center, served in the US Senate as a Congressional Science Fellow, and worked with local and tribal communities to develop GIS-based decision support systems for city planning, natural resource management, coastal management, and disaster response through the University of Wisconsin-Madison.
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