Is Your Perspective Also My Perspective? Enriching Prediction with Subjectivity

Julia Romberg


Abstract
Although argumentation can be highly subjective, the common practice with supervised machine learning is to construct and learn from an aggregated ground truth formed from individual judgments by majority voting, averaging, or adjudication. This approach leads to a neglect of individual, but potentially important perspectives and in many cases cannot do justice to the subjective character of the tasks. One solution to this shortcoming are multi-perspective approaches, which have received very little attention in the field of argument mining so far. In this work we present PerspectifyMe, a method to incorporate perspectivism by enriching a task with subjectivity information from the data annotation process. We exemplify our approach with the use case of classifying argument concreteness, and provide first promising results for the recently published CIMT PartEval Argument Concreteness Corpus.
Anthology ID:
2022.argmining-1.11
Volume:
Proceedings of the 9th Workshop on Argument Mining
Month:
October
Year:
2022
Address:
Online and in Gyeongju, Republic of Korea
Venue:
ArgMining
SIG:
Publisher:
International Conference on Computational Linguistics
Note:
Pages:
115–125
Language:
URL:
https://aclanthology.org/2022.argmining-1.11
DOI:
Bibkey:
Cite (ACL):
Julia Romberg. 2022. Is Your Perspective Also My Perspective? Enriching Prediction with Subjectivity. In Proceedings of the 9th Workshop on Argument Mining, pages 115–125, Online and in Gyeongju, Republic of Korea. International Conference on Computational Linguistics.
Cite (Informal):
Is Your Perspective Also My Perspective? Enriching Prediction with Subjectivity (Romberg, ArgMining 2022)
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PDF:
https://aclanthology.org/2022.argmining-1.11.pdf
Code
 juliaromberg/argmining2022