The growing popularity of Social Networking Sites (SNS) that are embedded with networked infrastructures serves as an ideal platform for developing a networked learning environment connecting geographically dispersed learners. Unlike the traditional learning systems which provide only limited sources of data, the learners engaged in virtual networked social environments tend to produce huge volumes of digital footprints that cannot be analyzed using conventional analytical techniques. Two new branches of analytical sciences -- Educational Data Mining (EDM) and Learning Analytics (LA) -- are being employed for processing digital data derived from online educational platforms in order to obtain meaningful inferences and data-driven insights.Hence, the present experimental study involving a small group of geographically dispersed learners intend to examine the engagement level and interaction patterns that occur within a feminist networked learning environment created in Facebook using popular EDM and learning analytical techniques such as K-means Clustering, Social network analysis and correlation mining. Upon analysis, it was found that the peer network influence played a vital role in activating passive learners, eventually leading to the development of a closely bound networked learning community over time.