Categorizing and measuring social ties

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Nelimarkka, Matti
dc.contributor.author Karikoski, Juuso
dc.date.accessioned 2014-02-18T10:00:34Z
dc.date.available 2014-02-18T10:00:34Z
dc.date.issued 2012
dc.identifier.citation Nelimarkka, Matti & Karikoski, Juuso. 2012. Categorizing and measuring social ties. RC33 Eighth International Conference on Social Science Methodology. en
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/12604
dc.description.abstract he analysis of social networks has boomed recently, mainly as online social networking systems such as Twitter allow researchers to access these data. However, the research is less and less focused on the fundamental question on the validity of the data and interpretation of the results. For example, Golder et al. (2007) use the word 'friend' in quotes while describing their results. To enhance the discussion around the validity of results, our work contributes a categorization of social network data. We also discuss the differences of the data sources, especially highlighting the fact that different data sources disclose different kinds of networks. Our approach is to examine social networks based on several sources of data, and thus acquire a richer data set. Based on this extended data set, we are more equipped to understand the social relations represented via links between nodes. After reviewing the existing literature, we make two observations of social relationships in online services. Firstly, the friendship data may be shared in public or with the specific group of users of that service - this may affect how people perceive and use these relationships, especially when compared with the private displays of relations (e.g., Donath & boyd, 2004). On the other hand, people interact only with part of their social relations (e.g., Golder et al., 2007) and research has started to focus from statical networks to more dynamical activity based networks (e.g., Huberman et al., 2009). Based on the existing literature, shortly discussed above, a 2x2 matrix can be developed. Relations may be public or private and active or passive. For instance, those relations with which you use Instant Messaging can be considered private and active whereas Facebook friends are passive and public. As they are different in this nature, also the conclusions based on the analysis should differ. After confirming that the data measure the phenomenon desired, one should use several kinds of data sources to really understand the social structures behind the group under study. We claim that multiple data sets should be used when measuring social relations. McPherson et al. (2001) have also concluded that the priority for future social network researchers should be to gather dynamic data on multiple social relations. By studying existing research and our own empirical data (e.g., Karikoski & Nelimarkka, 2011), we discuss the opportunities and challenges of using multiple data sets to cover the same group. en
dc.format.extent 18
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Aalto University en
dc.publisher Aalto-yliopisto fi
dc.relation.ispartof RC33 Eighth International Conference on Social Science Methodology en
dc.subject.other Communication en
dc.subject.other Computer science en
dc.subject.other Social sciences en
dc.title Categorizing and measuring social ties en
dc.type B3 Vertaisarvioimaton artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed
dc.contributor.school Perustieteiden korkeakoulu fi
dc.contributor.school School of Science en
dc.contributor.department Tietotekniikan tutkimuslaitos HIIT fi
dc.contributor.department Helsinki Institute for Information Technology HIIT en
dc.subject.keyword social ties en
dc.subject.keyword social network analysis en
dc.identifier.urn URN:NBN:fi:aalto-201402191437
dc.type.dcmitype text en
dc.type.version Final published version


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