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Research Confidential pulls back the curtain on this process, laying bare the sordid details of the research process, but doing so in a way that respects the ideals of social research and that provides useful lessons for young scholars. It should be required reading for our research methods courses.\"--Michael X. Delli Carpini, Dean, Annenberg School for Communication, University of Pennsylvania \"In this impressive volume, some of the brightest young lights in social research have taken us backstage to share what they learned from their innovative projects. Besides providing a wealth of help with methodological concerns, the book includes theoretical and career issues to consider when doing research. 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Critically, it will make new researchers aware of the actual challenges that they are likely to face in their work.\" --Christopher Winship, editor of Sociological Methods and Research and Professor of Sociology, Harvard University This collection of essays aims to fill a notable gap in the existing literature on research methods in the social sciences. While the methods literature is extensive, rarely do authors discuss the practical issues and challenges they routinely confront in the course of their research projects. As a result, editor Eszter Hargittai argues, each new cohort is forced to reinvent the wheel, making mistakes that previous generations have already confronted and resolved. Research Confidential seeks to address this failing by supplying new researchers with the kind of detailed practical information that can make or break a given project. 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"creatorType": "author", "firstName": "Alex (Sandy)", "lastName": "Pentland" }, { "creatorType": "author", "firstName": "David", "lastName": "Lazer" } ], "abstractNote": "Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.", "publicationTitle": "Proceedings of the National Academy of Sciences", "publisher": "", "place": "", "date": "09/08/2009", "volume": "106", "issue": "36", "section": "", "partNumber": "", "partTitle": "", "pages": "15274-15278", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "PNAS", "DOI": "10.1073/pnas.0900282106", "citationKey": "", "url": "http://www.pnas.org/content/106/36/15274", "accessDate": "2012-12-13T17:01:03Z", "PMID": "", "PMCID": "", "ISSN": "0027-8424, 1091-6490", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.pnas.org", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "engineering-social systems", "type": 1 }, { "tag": "reality mining", "type": 1 }, { "tag": "relational inference", "type": 1 }, { "tag": "relational scripts", "type": 1 }, { "tag": "social network analysis", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2012-12-14T17:13:47Z", "dateModified": "2012-12-14T17:13:47Z" } } ]