Taking long series of screenshots for capturing and studying smartphone users' phone usage and media consumption has recently attracted research attention due to its advantage of capturing rich contextual information from users' phone use journeys. However, that approach creates a high volume of screenshots that take very considerable time and effort to inspect and annotate, especially when the granularity of analysis is low: such as when distinguishing among media-content units (e.g, single FB posts) and detecting events in them. We therefore developed Screenshot Journey Auditor (SJA), a web application that identifies individual social media posts, and detects news items and other events of interest in them. It then visualizes users' journeys 'flow' among these media-content units. SJA also enables researchers/coders to collaboratively correct detections online. We evaluated SJA with five coders and received positive feedback on how the detections and visualizations made the analysis process more efficient and informative.