Crowd Prefers the Middle Path: A New IAA Metric for Crowdsourcing Reveals Turker Biases in Query Segmentation

Query segmentation, like text chunking, is the first step towards query understanding. In this study we explore the effectiveness of crowdsourcing for this task. Through carefully designed control experiments and Inter Annotator Agreement metrics for analysis of experimental data, we show that crowdsourcing may not be a suitable approach for query segmentation because the crowd seems to have a very strong bias towards dividing the query into roughly equal (often only two) parts. Similarly, in the case of hierarchical or nested segmentation, turkers have a strong preference towards balanced binary trees.

Dataset.zip
ZIP compressed file
Supplementary material.pdf
PDF file

In  Proceedings of ACL

Publisher  Association for Computational Linguistics

Details

TypeInproceedings
> Publications > Crowd Prefers the Middle Path: A New IAA Metric for Crowdsourcing Reveals Turker Biases in Query Segmentation