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Date: Sun, 19 May 2019 10:23:23 GMT
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URL: http://www.ox.ac.uk/news/2019-05-16-new-machine-learning-algorithm-can-predict-age-and-gender-just-your-twitter-profile
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Title: New machine learning algorithm can predict age and gender from just your Twitter profile | University of Oxford
Description: A new “demographic inference” tool developed by academics can make predictions based solely on the information in a person’s social media profile (i.e. screen name, biography, profile photo, and name). The tool—which works in 32 languages—could pave the way for views expressed on social media to be factored in to popular survey methods.
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Texto: New machine learning algorithm can predict age and gender from just your Twitter profile | University of Oxford Skip to main content Home Home Admissions Undergraduate Graduate Continuing education Research Divisions Research impact Libraries Innovation and Partnership Support for researchers Research in conversation Public Engagement with Research News & Events Events Science Blog Arts Blog Oxford and Brexit News releases for journalists Filming in Oxford Find An Expert About Organisation Facts and figures Oxford people Oxford Access International Oxford Building Our Future Jobs 牛津大学 Search News & Events Events Regular events in the University Year Race and the Curriculum Women of Achievement Science Blog Arts Blog Oxford and Brexit Latest University updates University to pay settlement fees for all EU staff EU referendum and Brexit: Analysis News releases for journalists Filming in Oxford Find An Expert New machine learning algorithm can predict age and gender from just your Twitter profile Image credit: Shutterstock Published 16 May 2019 Share This Tweet Share on Facebook Share on LinkedIn Share on Reddit Home News New machine learning algorithm can predict age and gender from just your Twitter profile New machine learning algorithm can predict age and gender from just your Twitter profile Research Society A new “demographic inference” tool developed by academics can make predictions based solely on the information in a person’s social media profile (i.e. screen name, biography, profile photo, and name). The tool—which works in 32 languages—could pave the way for views expressed on social media to be factored in to popular survey methods. Researchers at the University of Oxford, University of Michigan, University of Massachusetts, GESIS – Leibniz Institute for the Social Sciences, the Max Planck Institute, and Stanford University have developed a method to infer information about a social media account owner based on the information disclosed in their Twitter profile information. A new machine learning system —unveiled at the Web Conference in San Francisco this week—learned the patterns associated with different ages, genders, and between organisations and individuals from a data set of over four million Twitter accounts in 32 languages. This information was then combined with estimated locations and re-weighted against census data to produce more accurate estimates of population in 1,101 statistical regions across the EU. This could pave the way for a more representative understanding of people's views on key societal issues and topics, based on what they post on social media and attributed to specific geographical locations and demographic groups. Dr Scott Hale, Senior Research Fellow, Oxford Internet Institute, University of Oxford said: “Despite providing lots of data points, social media has long been an unreliable tool for understanding what issues are most important to a wider population given how people self-select into using any one platform. “This first study of its kind performs demographic predictions about a social media account’s owner based purely on the account’s profile information in 32 languages and then re-weights the online sample to be more similar to an offline population. “We see this as a significant step towards using social media to get a more accurate picture on the issues and topics that most interest the public and understanding which groups’ views are over- or under-represented.” This information and data underpinning this research has been made available in an open source library and you can test the inference tool at http://www.euagendas.org/m3demo . Latest Accelerating quantum technologies with materials processing at the atomic scale 17 May 2019 Oxford’s ‘Welsh College’ secures a £625,000 investment for access 17 May 2019 Oxford scoops BBSRC Innovator of the Year 2019 16 May 2019 New machine learning algorithm can predict age and gender from just your Twitter profile 16 May 2019 Oxford announces new Institute for Charity 15 May 2019 Further information Full paper: Demographic Inference and Representative Population Estimates from Multilingual Social Media Data All news Share This Tweet Share on Facebook Share on LinkedIn Share on Reddit Connect with us iTunes Youtube Facebook Twitter LinkedIn Weibo Instagram Medium The Conversation Information About Oxford University Strategic plan Oxford's research Fees and funding Libraries Museums and collections Open days Oxford glossary Statement on Modern Slavery Data privacy / GDPR Sport at Oxford Conferences at Oxford 牛津大学 Information For Prospective undergraduates Prospective graduate students Prospective Continuing Education students Prospective online/distance learning students Current Oxford students Current Oxford staff Oxford residents/Community Visitors/Tourists Media Alumni Teachers Parliamentarians Businesses/Partnerships Quick Links Contact search Jobs and vacancies Term dates Map Nexus365 email Giving to Oxford Oxford University Images © University of Oxford 2019 Contact us About this site Legal Privacy policy Cookie statement


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