To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulation experiments. These approaches extend previously proposed frameworks, including constraints and informed prior-based methods. Users should have a sense of control in HLTM systems, so we propose a control metric to measure whether refinement operations' results match users' expectations. Informed prior-based methods provide better control than constraints, but constraints yield higher quality topics.
@article{arxiv.1905.09864,
title = {Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models},
author = {Varun Kumar and Alison Smith-Renner and Leah Findlater and Kevin Seppi and Jordan Boyd-Graber},
journal= {arXiv preprint arXiv:1905.09864},
year = {2019}
}