BEGIN:VCALENDAR PRODID:-//Microsoft Corporation//Outlook 16.0 MIMEDIR//EN VERSION:2.0 METHOD:PUBLISH X-MS-OLK-FORCEINSPECTOROPEN:TRUE BEGIN:VTIMEZONE TZID:W. Europe Standard Time BEGIN:STANDARD DTSTART:16011028T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:16010325T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT CLASS:PUBLIC CREATED:20190402T080720Z DESCRIPTION:Minorities in Social and Information Networks\n \nAbstract\n \n Networks are the infrastructure of our social and professional life and al so of modern information systems where billions of documents and entities are interlinked.\nHowever\, not all nodes are equal in these networks. Oft en we observe attributes (e.g. gender or ethnicity) that define the group membership of a node.\nIn this talk I will explore the role of minorities in social networks and information networks\, provide empirical evidence f or the disadvantage of minorities and discuss factors that may place minor ities at a disadvantage.\n \nBio\n \nClaudia Wagner is an assistant profes sor (W1) in Computer Science at University Koblenz-Landau and the interim Scientific Director of the department Computational Social Science at GESI S - Leibniz Institute for the Social Sciences. Wagner received her PhD fro m Graz University of Technology in 2013\, before she joined GESIS as postd octoral researcher (2013-2016).\nPrior to that she conducted several inter national research internships\, among others at HP labs\, Xerox PARC and the Open University. To date\, she has been awarded substantial research f unding either as a PI or co-PI\, was awarded with a DOC-fFORTE fellowship from the Austrian Academy of Sciences and received four best paper awards (at ESWC 2010\, SocialCom 2012\, ICWSM 2014\, WebSci 2015).\nHer research focuses on computational methods and models for analyzing social issues (e .g. gender inequality\, sexism) and social phenomena (e.g. collective atte ntion\, culture) using digital traces.\n \n DTEND;TZID="W. Europe Standard Time":20190617T190000 DTSTAMP:20190402T080720Z DTSTART;TZID="W. Europe Standard Time":20190617T170000 LAST-MODIFIED:20190402T080720Z LOCATION:Aula Atle Technik\, Rechbauerstra├če 12/I\, 8010 Graz PRIORITY:5 SEQUENCE:0 SUMMARY;LANGUAGE=de:CS Talks #4 | Claudia Wagner TRANSP:OPAQUE UID:040000008200E00074C5B7101A82E008000000001096DEB63BE9D401000000000000000 010000000C0B081056BED304BBCB0FDF28C4E8955 X-ALT-DESC;FMTTYPE=text/html:

Minorities in Social and Information Netwo rks

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Abstract

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Networks are the infrastructure of our social and professiona l life and also of modern information systems where billions of documents and entities are interlinked.

However\, not all nodes are e qual in these networks. Often we observe attributes (e.g. gender or ethnic ity) that define the group membership of a node.

In this ta lk I will explore the role of minorities in social networks and informatio n networks\, provide empirical evidence for the disadvantage of minorities and discuss factors that may place minorities at a disadvantage.

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Bio

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Claudia Wagner is an assistant pr ofessor (W1) in Computer Science at University Koblenz-Landau and the inte rim Scientific Director of the department Computational Social Science at GESIS - Leibniz Institute for the Social Sciences. Wagner received her PhD from Graz University of Technology in 2013\, before she joined GESIS as p ostdoctoral researcher (2013-2016).

Prior to that she condu cted several international research internships\, among others at HP labs\ , Xerox PARC \; and the Open Uni versity. To date\, she has been awarded substantial research funding eithe r as a PI or co-PI\, was awarded with a DOC-fFORTE fellowship from the Austrian Academy of Sciences and received four best paper awards (at ESWC 2010\, SocialCom 2012\, I CWSM 2014\, WebSci 2015).

< p class=MsoNormal>Her res earch focuses on computational methods and models for analyzing social iss ues (e.g. gender inequality\, sexism) and social phenomena (e.g. collectiv e attention\, culture) using digital traces.

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