Do Differences in Values Influence Disagreements in Online Discussions?
This work addresses the challenge of improving online discussion quality for researchers and platform developers, but it is incremental as it builds on existing methods for value estimation and agreement prediction.
The study tackled the problem of understanding factors influencing disagreement in online discussions by investigating whether differences in personal values correlate with disagreement, finding that value profile dissimilarity correlates with disagreement in specific cases and including value information improves agreement prediction performance.
Disagreements are common in online discussions. Disagreement may foster collaboration and improve the quality of a discussion under some conditions. Although there exist methods for recognizing disagreement, a deeper understanding of factors that influence disagreement is lacking in the literature. We investigate a hypothesis that differences in personal values are indicative of disagreement in online discussions. We show how state-of-the-art models can be used for estimating values in online discussions and how the estimated values can be aggregated into value profiles. We evaluate the estimated value profiles based on human-annotated agreement labels. We find that the dissimilarity of value profiles correlates with disagreement in specific cases. We also find that including value information in agreement prediction improves performance.