A preliminary analysis on student postings on Facebook and blogs in an internship course in information management

Abstract

This study analyzes student postings on Facebook and blogs in the same internship course across six years in an Information Management program. A two-level coding scheme on knowledge management and socio-emotional support was adapted to encode the postings. Association rule mining was applied to discover relationships between code categories; automated classification models were built and evaluated in various compositions of the categories. Preliminary findings disclosed that students posted messages of emotional expressions and social support, as well as those showing knowledge capturing and knowledge sharing processes. Preliminary results of classification experiments demonstrate the feasibility of automated analysis. It is also found that postings in the two platforms, Facebook and blogs, are mostly indistinguishable except for those in the social support categories.