The emergence and near ubiquity of the misuse of social media platforms poses a variety of problems for the research community. One of the primary challenges is dealing with the volume and complexity of analyzing social media across multiple platforms, especially for researchers without computer science backgrounds. In this paper, we present SMAT, a hosted Web application that enables easy exploratory analysis across billions of social media posts. SMAT provides a middleware for Pushshift's back end data store that performs useful, but complicated aggregations and exports the results to an interactive analysis front end. This front end provides an easy, user friendly interface that enables fast, large scale exploratory analysis that can be deployed on cheap (or even free) cloud resources. In addition to presenting SMAT's architecture and functionality, we also demonstrate its usefulness via two use cases relevant to the research community focused on emergent dangerous social media phenomena. First, we show how SMAT can be used to help understand shifts in disand mis-information campaigns related to Syrian chemical weapons usage. Next, we explore how a decade old conspiracy theory has seen a resurgence in relation to the COVID-19 pandemic.