Learning to Adapt Domain Shifts of Moral Values via Instance Weighting

Xiaolei Huang, Alexandra Wormley, Adam Cohen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Classifying moral values in user-generated text from social media is critical in understanding community cultures and interpreting user behaviors of social movements. Moral values and language usage can change across the social movements; however, text classifiers are usually trained in source domains of existing social movements and tested in target domains of new social issues without considering the variations. In this study, we examine domain shifts of moral values and language usage, quantify the effects of domain shifts on the morality classification task, and propose a neural adaptation framework via instance weighting to improve cross-domain classification tasks. The quantification analysis suggests a strong correlation between morality shifts, language usage, and classification performance. We evaluate the neural adaptation framework on a public Twitter data across 7 social movements and gain classification improvements up to 12.1%. Finally, we release a new data of the COVID-19 vaccine labeled with moral values and evaluate our approach on the new target domain. For the case study of the COVID-19 vaccine, our adaptation framework achieves up to 5.26% improvements over neural baselines. This is the first study to quantify impacts of moral shifts, propose adaptive framework to model the shifts, and conduct a case study to model COVID-19 vaccine-related behaviors from moral values.

Original languageEnglish (US)
Title of host publicationHT 2022
Subtitle of host publication33rd ACM Conference on Hypertext and Social Media - Co-located with ACM WebSci 2022 and ACM UMAP 2022
PublisherAssociation for Computing Machinery, Inc
Pages121-131
Number of pages11
ISBN (Electronic)9781450392334
DOIs
StatePublished - Jun 28 2022
Externally publishedYes
Event33rd ACM Conference on Hypertext and Social Media, HT 2022 - Co-located with ACM WebSci 2022 and ACM UMAP 2022 - Virtual, Online, Spain
Duration: Jun 28 2022Jul 1 2022

Publication series

NameHT 2022: 33rd ACM Conference on Hypertext and Social Media - Co-located with ACM WebSci 2022 and ACM UMAP 2022

Conference

Conference33rd ACM Conference on Hypertext and Social Media, HT 2022 - Co-located with ACM WebSci 2022 and ACM UMAP 2022
Country/TerritorySpain
CityVirtual, Online
Period6/28/227/1/22

Keywords

  • adaptation
  • classification
  • domain variation
  • instant weighting
  • moral values
  • morality

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Fingerprint

Dive into the research topics of 'Learning to Adapt Domain Shifts of Moral Values via Instance Weighting'. Together they form a unique fingerprint.

Cite this