Sunbelt XXXI International Network for Social Network ... - INSNA

Online And Offline Ego‐centered Network Data CollectionVernon, Matthew C.; Danon, Leon; House, Thomas A.; Read, Jonathan M.; Keeling, Matt J.Online Social NetworksData Collection, Network Data, Contact Diary, Ego‐centered Networks, Online Survey, epidemiologyTHURS.AM1The Social Contact Study was a cross‐sectional study of the contact patterns of more than five thousand people from the United Kingdom. It employed postaland electronic questionnaires to elicit data about a responder's conversational and tactile encounters on a particular day, as well as the responder's view of thesocial encounters between their contacts. This study was designed to collect large‐scale data on the contact patterns of individuals in the UK that would besuitable for modelling the transmission of infectious diseases such as influenza; during the data collection period, a facebook tie‐in was developed to increaseonline participation in the survey. In this paper, we compare and contrast the offline and online participants (the latter being partitioned into those whoresponded before the facebook tie‐in, and those who responded after it was launched). In particular, we show that these responder groups differ in theirdemography, as well as in the contact patterns that they report. Further, we show how demographic data can be used to make the different participant groupsmore comparable and to assess the impact of response mode on the supplied network data. These findings give us confidence in the validity of combiningoffline and online techniques to gather large‐scale contact data.Online FriendDships In The Netherlands: Analysis Of A National‐level NetworkCorten, RenseOnline Social NetworksLarge‐scale Networks, Online NetworksFRI.AM1Progress in research on friendship networks has long been hampered by data limitations. Most earlier studies use either a sample of ego‐networks, orcomplete network data on a relatively small group (e.g., a single organization). The advent of online social networking services such as Friendster andFacebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. In this study, we use complete network datafrom a popular online social networking service in the Netherlands, comprising over 8,000,000 nodes and hundreds of millions of online friendship relations. Inthe first study of its kind for the Netherlands, we examine the structure of this network in terms of the degree distribution, average distance, clustering, andcommunity structure. First results indicate that this network shares features of other large complex networks, but also deviates in other respects.