Are Words Commensurate with Actions? Quantifying Commitment to a Cause from Online Public Messaging

TL;DR

This paper introduces a text classification method to measure the commitment level of public messages on causes and compares it with external action-based ratings to identify discrepancies and inauthentic messaging.

Contribution

It presents a novel approach to quantify commitment in online messaging and assess its alignment with actual actions of entities, improving transparency.

Findings

High-commitment messages better predict true commitment.

Discrepancies reveal inauthentic or strategic messaging.

Method can identify entities with misaligned messaging and actions.

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.