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This paper summarises the analyses of participant interaction within the Twitter microblogging environment. The study employs longitudinal probabilistic social network analysis (SNA) techniques to identify the patterns and trends of network dynamics. It explores the associations of student achievement records with the observed network. The results indicate tendencies towards: [i] reciprocal interaction, and [ii] adoption of a selective approach in communication over time, implying that students tend to communicate with fewer peers over time. The evaluations that examine achievement score attributes indicate [iii] network homogeneity and popularity effects associated to achievement scores - suggesting greater interaction among students of similar levels and more attention to higher achieving students.