Tweet Trajectory and AMPS-based Contextual Cues can Help Users Identify Misinformation

Well-intentioned users sometimes enable the spread of misinformation due to limited context about where the information originated and/or why it is spreading. Building upon recommendations based on prior research about tackling misinformation, we explore the potential to support media literacy through platform design. We develop and design an intervention consisting of a tweet trajectory-to illustrate how information reached a user-and contextual cues-to make credibility judgments about accounts that amplify, manufacture, produce or situate in the vicinity of problematic content (AMPS). Using a research through design approach, we demonstrate how the proposed intervention can help discern credible actors, challenge blind faith amongst online friends, evaluate the cost of associating with online actors, and expose hidden agendas. Such facilitation of credibility assessment can encourage more responsible sharing of content. Through our findings, we argue for using trajectory-based designs to support informed information sharing, advocate for feature updates that nudge users with reflective cues, and promote platform-driven media literacy.

CCS Concepts: • Human-centered computing → Empirical studies in HCI; Collaborative and social computing systems and tools.