Comparing Community Structure to Characteristics in Online Collegiate Social Networks

Comparing Community Structure to Characteristics in Online Collegiate Social Networks. Traud, A. L., Kelsic, E. D., Mucha, P. J., & family=Porter , g. 53(3):17.

Paper doi abstract bibtex

We study the structure of social networks of students by examining the graphs of Facebook "friendships" at five American universities at a single point in time. We investigate each single-institution network's community structure and employ graphical and quantitative tools, including standardized pair-counting methods, to measure the correlations between the network communities and a set of self-identified user characteristics (residence, class year, major, and high school). We review the basic properties and statistics of the pair-counting indices employed and recall, in simplified notation, a useful analytical formula for the z-score of the Rand coefficient. Our study illustrates how to examine different instances of social networks constructed in similar environments, emphasizes the array of social forces that combine to form "communities," and leads to comparative observations about online social lives that can be used to infer comparisons about offline social structures. In our illustration of this methodology, we calculate the relative contributions of different characteristics to the community structure of individual universities and subsequently compare these relative contributions at different universities, measuring for example the importance of common high school affiliation to large state universities and the varying degrees of influence common major can have on the social structure at different universities. The heterogeneity of communities that we observe indicates that these networks typically have multiple organizing factors rather than a single dominant one.

@article{traudComparingCommunityStructure2008,
  title = {Comparing {{Community Structure}} to {{Characteristics}} in {{Online Collegiate Social Networks}}},
  volume = {53},
  issn = {0036-1445},
  url = {http://arxiv.org/abs/0809.0690},
  doi = {10.1137/080734315},
  abstract = {We study the structure of social networks of students by examining the graphs of Facebook "friendships" at five American universities at a single point in time. We investigate each single-institution network's community structure and employ graphical and quantitative tools, including standardized pair-counting methods, to measure the correlations between the network communities and a set of self-identified user characteristics (residence, class year, major, and high school). We review the basic properties and statistics of the pair-counting indices employed and recall, in simplified notation, a useful analytical formula for the z-score of the Rand coefficient. Our study illustrates how to examine different instances of social networks constructed in similar environments, emphasizes the array of social forces that combine to form "communities," and leads to comparative observations about online social lives that can be used to infer comparisons about offline social structures. In our illustration of this methodology, we calculate the relative contributions of different characteristics to the community structure of individual universities and subsequently compare these relative contributions at different universities, measuring for example the importance of common high school affiliation to large state universities and the varying degrees of influence common major can have on the social structure at different universities. The heterogeneity of communities that we observe indicates that these networks typically have multiple organizing factors rather than a single dominant one.},
  number = {3},
  journaltitle = {SIAM Review},
  date = {2008},
  pages = {17},
  keywords = {080734315,10,1137,2008,62h17,82-08,91-08,91d30,accepted for publication,ams subject classifications,august,community structure,contingency tables,doi,in revised form,networks,pair counting,received by the editors,september 4},
  author = {Traud, Amanda L. and Kelsic, Eric D. and Mucha, Peter J. and family=Porter, given=Mason, prefix=a., useprefix=false},
  file = {/home/dimitri/Nextcloud/Zotero/storage/7NA4GN3X/Traud et al. - 2008 - Comparing Community Structure to Characteristics in Online Collegiate Social Networks.pdf}
}

Downloads: 0

{"_id":"igiet6HaNSSp7En4d","bibbaseid":"traud-kelsic-mucha-familyporter-comparingcommunitystructuretocharacteristicsinonlinecollegiatesocialnetworks","authorIDs":[],"author_short":["Traud, A. L.","Kelsic, E. D.","Mucha, P. J.","family=Porter , g."],"bibdata":{"bibtype":"article","type":"article","title":"Comparing Community Structure to Characteristics in Online Collegiate Social Networks","volume":"53","issn":"0036-1445","url":"http://arxiv.org/abs/0809.0690","doi":"10.1137/080734315","abstract":"We study the structure of social networks of students by examining the graphs of Facebook \"friendships\" at five American universities at a single point in time. We investigate each single-institution network's community structure and employ graphical and quantitative tools, including standardized pair-counting methods, to measure the correlations between the network communities and a set of self-identified user characteristics (residence, class year, major, and high school). We review the basic properties and statistics of the pair-counting indices employed and recall, in simplified notation, a useful analytical formula for the z-score of the Rand coefficient. Our study illustrates how to examine different instances of social networks constructed in similar environments, emphasizes the array of social forces that combine to form \"communities,\" and leads to comparative observations about online social lives that can be used to infer comparisons about offline social structures. In our illustration of this methodology, we calculate the relative contributions of different characteristics to the community structure of individual universities and subsequently compare these relative contributions at different universities, measuring for example the importance of common high school affiliation to large state universities and the varying degrees of influence common major can have on the social structure at different universities. The heterogeneity of communities that we observe indicates that these networks typically have multiple organizing factors rather than a single dominant one.","number":"3","journaltitle":"SIAM Review","date":"2008","pages":"17","keywords":"080734315,10,1137,2008,62h17,82-08,91-08,91d30,accepted for publication,ams subject classifications,august,community structure,contingency tables,doi,in revised form,networks,pair counting,received by the editors,september 4","author":[{"propositions":[],"lastnames":["Traud"],"firstnames":["Amanda","L."],"suffixes":[]},{"propositions":[],"lastnames":["Kelsic"],"firstnames":["Eric","D."],"suffixes":[]},{"propositions":[],"lastnames":["Mucha"],"firstnames":["Peter","J."],"suffixes":[]},{"propositions":["family=Porter"],"lastnames":[],"firstnames":["given=Mason"],"suffixes":["prefix=a.",",","useprefix=false"]}],"file":"/home/dimitri/Nextcloud/Zotero/storage/7NA4GN3X/Traud et al. - 2008 - Comparing Community Structure to Characteristics in Online Collegiate Social Networks.pdf","bibtex":"@article{traudComparingCommunityStructure2008,\n title = {Comparing {{Community Structure}} to {{Characteristics}} in {{Online Collegiate Social Networks}}},\n volume = {53},\n issn = {0036-1445},\n url = {http://arxiv.org/abs/0809.0690},\n doi = {10.1137/080734315},\n abstract = {We study the structure of social networks of students by examining the graphs of Facebook \"friendships\" at five American universities at a single point in time. We investigate each single-institution network's community structure and employ graphical and quantitative tools, including standardized pair-counting methods, to measure the correlations between the network communities and a set of self-identified user characteristics (residence, class year, major, and high school). We review the basic properties and statistics of the pair-counting indices employed and recall, in simplified notation, a useful analytical formula for the z-score of the Rand coefficient. Our study illustrates how to examine different instances of social networks constructed in similar environments, emphasizes the array of social forces that combine to form \"communities,\" and leads to comparative observations about online social lives that can be used to infer comparisons about offline social structures. In our illustration of this methodology, we calculate the relative contributions of different characteristics to the community structure of individual universities and subsequently compare these relative contributions at different universities, measuring for example the importance of common high school affiliation to large state universities and the varying degrees of influence common major can have on the social structure at different universities. The heterogeneity of communities that we observe indicates that these networks typically have multiple organizing factors rather than a single dominant one.},\n number = {3},\n journaltitle = {SIAM Review},\n date = {2008},\n pages = {17},\n keywords = {080734315,10,1137,2008,62h17,82-08,91-08,91d30,accepted for publication,ams subject classifications,august,community structure,contingency tables,doi,in revised form,networks,pair counting,received by the editors,september 4},\n author = {Traud, Amanda L. and Kelsic, Eric D. and Mucha, Peter J. and family=Porter, given=Mason, prefix=a., useprefix=false},\n file = {/home/dimitri/Nextcloud/Zotero/storage/7NA4GN3X/Traud et al. - 2008 - Comparing Community Structure to Characteristics in Online Collegiate Social Networks.pdf}\n}\n\n","author_short":["Traud, A. L.","Kelsic, E. D.","Mucha, P. J.","family=Porter , g."],"key":"traudComparingCommunityStructure2008","id":"traudComparingCommunityStructure2008","bibbaseid":"traud-kelsic-mucha-familyporter-comparingcommunitystructuretocharacteristicsinonlinecollegiatesocialnetworks","role":"author","urls":{"Paper":"http://arxiv.org/abs/0809.0690"},"keyword":["080734315","10","1137","2008","62h17","82-08","91-08","91d30","accepted for publication","ams subject classifications","august","community structure","contingency tables","doi","in revised form","networks","pair counting","received by the editors","september 4"],"downloads":0},"bibtype":"article","biburl":"https://raw.githubusercontent.com/dlozeve/newblog/master/bib/all.bib","creationDate":"2020-01-08T20:39:39.033Z","downloads":0,"keywords":["080734315","10","1137","2008","62h17","82-08","91-08","91d30","accepted for publication","ams subject classifications","august","community structure","contingency tables","doi","in revised form","networks","pair counting","received by the editors","september 4"],"search_terms":["comparing","community","structure","characteristics","online","collegiate","social","networks","traud","kelsic","mucha","family=porter "],"title":"Comparing Community Structure to Characteristics in Online Collegiate Social Networks","year":null,"dataSources":["3XqdvqRE7zuX4cm8m"]}