citation.cff

cff-version: 1.3.3
message: >-
  If you use this software in your research, please cite both the software
  and the original article listed below.
title: Crowd_Frame
type: software
authors:
  - family-names: Soprano
    given-names: Michael
    orcid: https://orcid.org/0000-0002-7337-7592
  - family-names: Roitero
    given-names: Kevin
    orcid: https://orcid.org/0000-0002-9191-3280
  - family-names: Bombassei De Bona
    given-names: Francesco
  - family-names: Mizzaro
    given-names: Stefano
    orcid: https://orcid.org/0000-0002-2852-168X
repository-code: https://github.com/Miccighel/Crowd_Frame
url: https://doi.org/10.1145/3488560.3502182
abstract: >-
  Crowd_Frame is a framework that enables the development and deployment of
  complex crowdsourcing tasks in a simple and customizable way, making it
  easier for researchers and practitioners to collect high-quality human
  annotations across multiple platforms.
version: 1.3.3
date-released: 2026-02-12

preferred-citation:
  type: inproceedings
  authors:
    - family-names: Soprano
      given-names: Michael
      orcid: https://orcid.org/0000-0002-7337-7592
    - family-names: Roitero
      given-names: Kevin
      orcid: https://orcid.org/0000-0002-9191-3280
    - family-names: Bombassei De Bona
      given-names: Francesco
    - family-names: Mizzaro
      given-names: Stefano
      orcid: https://orcid.org/0000-0002-2852-168X
  title: "Crowd_Frame: A Simple and Complete Framework to Deploy Complex Crowdsourcing Tasks Off-the-Shelf"
  year: 2022
  booktitle: "Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining"
  publisher:
    name: Association for Computing Machinery
    address: New York, NY, USA
  pages: 1605-1608
  doi: 10.1145/3488560.3502182
  url: https://doi.org/10.1145/3488560.3502182
  isbn: 9781450391320
  series: WSDM '22
  location: Virtual Event, AZ, USA