Presentation Type
Oral Presentation
Start Date
5-8-2013 12:30 PM
End Date
5-8-2013 2:00 PM
Subjects
Reconstructability Analysis, Information Theory, Probabilistic graphical modeling, Multivariate analysis discrete multivariate modeling, Data mining
Abstract
Reconstructability analysis (RA) is proposed as a complementary method for evaluating social network-related phenomena. Longitudinal records of social behavior expression among members of a social network are commonly represented as a set of social network analysis (SNA) connections, but might also be usefully represented as a set of associations derived through RA methods. Reconstructability Analysis identifies individuals as being associated when their behavior patterns appear coordinated–a representation that is unavailable with standard SNA. To explore the potential usefulness of RA for analyzing social behaviors, simulated behavior patterns were evaluated with both SNA and RA, and the results were compared. Several RA data formats were tested, as RA cases can be defined by (a) individual or (b) synchronous behavior expression, or by (c) pairwise or (d) group level interactions. Associations derived with each data format were compared with the connections captured in a routine SNA adjacency matrix. Highest agreement between the two methods was found when cases were defined as instances of behavior expression at the group level. In addition, RA was shown to be able to derive triadic and higher-order associations among individuals, as well as sets of individuals whose behavior patterns were positively or negatively associated. Thus, RA appears to offer several capabilities to the study of social network-related phenomena that are not available with standard SNA techniques. Reconstructability analysis holds promise for advancing research on social behaviors, and can likely complement many of the efforts that are currently being made with SNA.
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Persistent Identifier
http://archives.pdx.edu/ds/psu/9487
Included in
Exploring the Application of Reconstructability Analysis to Behavior Expression Data from a Social Network
Reconstructability analysis (RA) is proposed as a complementary method for evaluating social network-related phenomena. Longitudinal records of social behavior expression among members of a social network are commonly represented as a set of social network analysis (SNA) connections, but might also be usefully represented as a set of associations derived through RA methods. Reconstructability Analysis identifies individuals as being associated when their behavior patterns appear coordinated–a representation that is unavailable with standard SNA. To explore the potential usefulness of RA for analyzing social behaviors, simulated behavior patterns were evaluated with both SNA and RA, and the results were compared. Several RA data formats were tested, as RA cases can be defined by (a) individual or (b) synchronous behavior expression, or by (c) pairwise or (d) group level interactions. Associations derived with each data format were compared with the connections captured in a routine SNA adjacency matrix. Highest agreement between the two methods was found when cases were defined as instances of behavior expression at the group level. In addition, RA was shown to be able to derive triadic and higher-order associations among individuals, as well as sets of individuals whose behavior patterns were positively or negatively associated. Thus, RA appears to offer several capabilities to the study of social network-related phenomena that are not available with standard SNA techniques. Reconstructability analysis holds promise for advancing research on social behaviors, and can likely complement many of the efforts that are currently being made with SNA.