Abstract

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.

Citation

@InProceedings{wang2017words,
  author =       {Zhao Wang and Jennifer Cutler and Aron Culotta},
  title =        {Are Words Commensurate with Actions? {Q}uantifying Commitment to a Cause from Online Public Messaging},
  booktitle = {Proceedings of the ACUMEN Workshop at the 17th {IEEE} International Conference on Data Mining (ICDM)},
  year =         2017,
}