| Vol-2932 urn:nbn:de:0074-2932-5 Copyright © 2021 for the individual papers by the papers' authors. Copyright © 2021 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# CSW 2021
Crowd Science Workshop: Trust, Ethics, and Excellence in Crowdsourced Data Management at Scale

### Proceedings of the 2nd Crowd Science Workshop: Trust, Ethics, and Excellence in Crowdsourced Data Management at Scale
co-located with 47th International Conference on Very Large Data Bases (VLDB 2021)

### Copenhagen, Denmark, August 20, 2021.

Edited by

### Dmitry Ustalov *
Fabio Casati **
Alexey Drutsa ***
Ivan Stelmakh ****
Nikita Pavlichenko ***
Daria Baidakova ***

* Yandex, 195027 Saint Petersburg, Russia
** ServiceNow, 2225 Santa Clara, California, USA
*** Yandex, 119021 Moscow, Russia
**** Carnegie Mellon University, 15213 Pittsburgh, Pennsylvania, USA

## Table of Contents

- Preface
  Summary: There were 11 papers submitted for peer-review to this workshop. Out of these, 7 papers were accepted for this volume, 5 as regular papers and 2 as short papers.

### Session 1: Shared Task

- VLDB 2021 Crowd Science Challenge on Aggregating Crowdsourced Audio Transcriptions 1-7
  Dmitry Ustalov, Nikita Pavlichenko, Ivan Stelmakh, Dmitriy Kuznetsov
- Fine-Tuning Pre-Trained Language Model for Crowdsourced Texts Aggregation 8-14
  Mikhail Orzhenovskii
- Noisy Text Sequences Aggregation as a Summarization Subtask 15-20
  Sergey Pletenev

### Session 2: Regular Papers

- A Multi-Objective Clustering Ensemble Approach for Crowdsourced Clustering 21-34
  Sujoy Chatterjee
- Crowdsourcing of Parallel Corpora: the Case of Style Transfer for Detoxification 35-49
  Daryna Dementieva, Sergey Ustyantsev, David Dale, Olga Kozlova, Nikita Semenov, Alexander Panchenko, Varvara Logacheva
- Training-Induced Class Imbalance in Crowdsourced Data 50-59
  Shawn Ogunseye, Jeffrey Parsons, Doyinsola Afolabi
- Aggregation of Crowdsourced Ontology-Based Item Descriptions by Hierarchical Voting 60-71
  Andrew Ponomarev
- Finer Granularity Means Better Data: a Crowdsourcing Lab Experiment 72-86
  Ryan Murphy, Jeffrey Parsons

2021-08-17: submitted by Dmitry Ustalov, metadata incl. bibliographic data published under Creative Commons CC0
2021-08-19: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|