Interpersonal Justice and Social Media: A Computationally Intensive Investigation

Social media use in social justice movements involves more than sharing perspectives; it shapes how justice is pursued in digital spaces. Because these dynamics remain understudied, we examine a “social media trial” surrounding three injustice events in a student movement that gained international attention after students were arrested on sedition charges. Participants used social media to sustain engagement and advance their cause while emphasizing interpersonal justice—respectful and dignified treatment (Colquitt, 2001).
Existing digital social justice research is fragmented and lacks interdisciplinary integration (Powell et al., 2018). Drawing on the interdisciplinary strengths of the IS field, we integrate insights from computer science, sociology, political science, and media studies. Although social media can promote fairness, it also reproduces injustices tied to gender, caste, and race (e.g., Fileborn & Loney-Howes, 2020).
Using computationally intensive theory construction methods (Miranda et al., 2022), we analyze Twitter data with topic modeling (LDA) to identify key themes across the three events, and semantic network analysis to examine relationships among them. Our findings show how themes evolve and interact following each injustice event, illustrating the digital dynamics of interpersonal justice and contention.
Building on research on collective engagement, protest cycles, and trolling, this case highlights how movements challenge dominant ideologies and power structures while navigating digital conflicts. It contributes to understanding how social media shapes justice-seeking processes and underscores the need for further interdisciplinary research in digital social justice.