Towards crowdsourcing and cooperation in linguistic resources

TL;DR

This paper explores how incorporating cooperation into crowdsourcing can enhance the development of linguistic resources, providing a taxonomy review, recommendations, and evidence of effectiveness through a Russian linguistic resource.

Contribution

It introduces the concept of cooperation into crowdsourcing taxonomies for linguistic resources and demonstrates its effectiveness with empirical evidence.

Findings

Cooperation increases annotator engagement and data quality.

Incorporating cooperation into crowdsourcing improves resource development.

Empirical evidence from a Russian linguistic resource supports these claims.

Abstract

Linguistic resources can be populated with data through the use of such approaches as crowdsourcing and gamification when motivated people are involved. However, current crowdsourcing genre taxonomies lack the concept of cooperation, which is the principal element of modern video games and may potentially drive the annotators' interest. This survey on crowdsourcing taxonomies and cooperation in linguistic resources provides recommendations on using cooperation in existent genres of crowdsourcing and an evidence of the efficiency of cooperation using a popular Russian linguistic resource created through crowdsourcing as an example.