@inproceedings{b0f48c1580d64683ae1fc8ccda59c303,
title = "Are words commensurate with actions? Quantifying commitment to a cause from online public messaging",
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.",
keywords = "Cause, Commitment, Public messaging",
author = "Zhao Wang and Jennifer Cutler and Aron Culotta",
note = "Funding Information: Anonymous reviewers helped improve this paper. This research was funded in part by the National Science Foundation under grants #IIS-1526674 and #IIS-1618244.; 17th IEEE International Conference on Data Mining Workshops, ICDMW 2017 ; Conference date: 18-11-2017 Through 21-11-2017",
year = "2017",
month = dec,
day = "15",
doi = "10.1109/ICDMW.2017.148",
language = "English (US)",
series = "IEEE International Conference on Data Mining Workshops, ICDMW",
publisher = "IEEE Computer Society",
pages = "1050--1057",
editor = "Raju Gottumukkala and George Karypis and Vijay Raghavan and Xindong Wu and Lucio Miele and Srinivas Aluru and Xia Ning and Guozhu Dong",
booktitle = "Proceeding - 17th IEEE International Conference on Data Mining Workshops, ICDMW 2017",
address = "United States",
}