# Measuring the Similarity of Sentential Arguments in Dialog

Source: [Measuring the Similarity of Sentential Arguments in Dialog](<https://www.sota2.com/research/paper/68fa63f21e209131cea01bb4>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T05:53:50.473Z

Authors: Amita Misra, Brian Ecker, Marilyn A. Walker

Published: 2017-09-06T17:15:49.000Z

## Abstract

When people converse about social or political topics, similar arguments are often paraphrased by different speakers, across many different conversations. Debate websites produce curated summaries of arguments on such topics; these summaries typically consist of lists of sentences that represent frequently paraphrased propositions, or labels capturing the essence of one particular aspect of an argument, e.g. Morality or Second Amendment. We call these frequently paraphrased propositions ARGUMENT FACETS. Like these curated sites, our goal is to induce and identify argument facets across multiple conversations, and produce summaries. However, we aim to do this automatically. We frame the problem as consisting of two steps: we first extract sentences that express an argument from raw social media dialogs, and then rank the extracted arguments in terms of their similarity to one another. Sets of similar arguments are used to represent argument facets. We show here that we can predict ARGUMENT FACET SIMILARITY with a correlation averaging 0.63 compared to a human topline averaging 0.68 over three debate topics, easily beating several reasonable baselines.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Argument Facet Similarity on AFS (10-fold Cross-Validation)](<https://www.sota2.com/research/sota/argument-facet-similarity-on-afs-10-fold-cross-validation.md>): Argument Facet Similarity; Argument Facet Similarity (AFS) (10-fold Cross-Validation); Pearson Correlation Coefficient: 63.33.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1709.01887>)

[PDF](<https://arxiv.org/pdf/1709.01887.pdf>)