  Public entities such as companies and politicians increasingly use online
social networks to communicate directly with their constituencies. Often, this
public messaging is aimed at aligning the entity with a particular cause or
issue, such as the environment or public health. However, as a consumer or
voter, it can be difficult to assess an entity's true commitment to a cause
based on public messaging. In this paper, we present a text classification
approach to categorize a message according to its commitment level toward a
cause. We then compare the volume of such messages with external ratings based
on entities' actions (e.g., a politician's voting record with respect to the
environment or a company's rating from environmental non-profits). We find that
by distinguishing between low- and high- level commitment messages, we can more
reliably identify truly committed entities. Furthermore, by measuring the
discrepancy between classified messages and external ratings, we can identify
entities whose public messaging does not align with their actions, thereby
providing a methodology to identify potentially "inauthentic" messaging
campaigns.
