Michelle X. Zhou, Jeffrey Nichols, T. Dignan, Steve Lohr, J. Golbeck, J. Pennebaker
{"title":"从社交媒体中发现个性特征的机会和风险","authors":"Michelle X. Zhou, Jeffrey Nichols, T. Dignan, Steve Lohr, J. Golbeck, J. Pennebaker","doi":"10.1145/2559206.2579408","DOIUrl":null,"url":null,"abstract":"With the emergence of social media and the availability of big data, there has been much interest in mining the digital footprints left by users to predict personality traits (e.g., introvert and idealistic) and gain a deeper understanding of individuals. While such understanding will enable hyper-personalized computing, such as personality-based marketing, the use of this technology will have far-reaching social implications that could affect almost every aspect of our lives. For example, personality traits mined from social media could be used to guide hiring and promotion decisions or decide who is admitted into top academic programs. The risks of using derived personality traits are potentially high, particular due to factors such as the veracity of data collected from social media, imperfections in prediction algorithms, and a lack of control over how, when, and to whom anyone's personality traits might be exposed. We will use this panel to bring together experts from the fields of Psychology, Social Science, Computer Science, along with the CHI community, to discuss and debate the opportunities and risks of personality discovery from social media and the implications on technical communities and our society at large.","PeriodicalId":125796,"journal":{"name":"CHI '14 Extended Abstracts on Human Factors in Computing Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Opportunities and risks of discovering personality traits from social media\",\"authors\":\"Michelle X. Zhou, Jeffrey Nichols, T. Dignan, Steve Lohr, J. Golbeck, J. Pennebaker\",\"doi\":\"10.1145/2559206.2579408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the emergence of social media and the availability of big data, there has been much interest in mining the digital footprints left by users to predict personality traits (e.g., introvert and idealistic) and gain a deeper understanding of individuals. While such understanding will enable hyper-personalized computing, such as personality-based marketing, the use of this technology will have far-reaching social implications that could affect almost every aspect of our lives. For example, personality traits mined from social media could be used to guide hiring and promotion decisions or decide who is admitted into top academic programs. The risks of using derived personality traits are potentially high, particular due to factors such as the veracity of data collected from social media, imperfections in prediction algorithms, and a lack of control over how, when, and to whom anyone's personality traits might be exposed. We will use this panel to bring together experts from the fields of Psychology, Social Science, Computer Science, along with the CHI community, to discuss and debate the opportunities and risks of personality discovery from social media and the implications on technical communities and our society at large.\",\"PeriodicalId\":125796,\"journal\":{\"name\":\"CHI '14 Extended Abstracts on Human Factors in Computing Systems\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CHI '14 Extended Abstracts on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2559206.2579408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CHI '14 Extended Abstracts on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2559206.2579408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Opportunities and risks of discovering personality traits from social media
With the emergence of social media and the availability of big data, there has been much interest in mining the digital footprints left by users to predict personality traits (e.g., introvert and idealistic) and gain a deeper understanding of individuals. While such understanding will enable hyper-personalized computing, such as personality-based marketing, the use of this technology will have far-reaching social implications that could affect almost every aspect of our lives. For example, personality traits mined from social media could be used to guide hiring and promotion decisions or decide who is admitted into top academic programs. The risks of using derived personality traits are potentially high, particular due to factors such as the veracity of data collected from social media, imperfections in prediction algorithms, and a lack of control over how, when, and to whom anyone's personality traits might be exposed. We will use this panel to bring together experts from the fields of Psychology, Social Science, Computer Science, along with the CHI community, to discuss and debate the opportunities and risks of personality discovery from social media and the implications on technical communities and our society at large.