Organization, Information and Learning Sciences ETDs

Publication Date

Summer 7-13-2018


The three research papers completed as part of this dissertation explore how people contributing to #BlackLivesMatter build knowledge, using social construction of knowledge (SCK), and what they are building knowledge about, using critical consciousness, because understanding how these processes play out on Twitter provides a way for others to understand this social movement. Paper 1 describes a new methodological approach to combining social network analysis (SNA) and social learning analytics to assess SCK. The sequential mixed method design begins by conducting a content analysis according to the Interaction Analysis Model (IAM). The results of the content analysis yield descriptive data that can be used to conduct SNA and social learning analytics.

The purpose of Paper 2 was to use the typology of digital activism actions identified by Penney and Dadas (2014) from interviews with digital activists to validate them in a quantitative study. Paper 2 found that the actions taken by people who are helping to facilitate face-to-face action (p < .0000001 , r = -0.076) or provide face-to-face updates (p < .0000001 , r = -0.060) were negatively correlated with the actions of people who were facilitating online actions suggesting that digital activists should be treated as a unique population of activists.

Paper 3 used the outcomes of a content analysis and lexicon analysis performed on #BlackLivesMatter data to determine 1) the levels of SCK and critical consciousness present in online data and 2) social learning analytics to ascertain the extent that SCK and critical consciousness can predict social action. Results of the content analysis and lexicon analysis found all levels of SCK and critical consciousness in the data. Results of social learning analytics conducted using Naïve Bayes classification indicate that SCK and critical consciousness can only predict information sharing behaviors of online social action like personal opinions, forwarding information, and engaging in discussion. Evidence of information sharing behaviors on Twitter provides a high degree of confidence that further research including replies and other interactions between users will reveal robust SCK.

Degree Name

Organization, Information and Learning Sciences

Level of Degree


Department Name

Organization, Information & Learning Sciences

First Committee Member (Chair)

Charlotte "Lani" Gunawardena

Second Committee Member

Vanessa Svihla

Third Committee Member

Nick Flor

Fourth Committee Member

Peter Jurkat




Social Learning Analytics, Interaction Analysis Model, Critical Consciousness, Network of Practice, #BlackLivesMatter, Social Action

Document Type