How Does the Crowd Impact the Model? A Tool for Raising Awareness of Social Bias in Crowdsourced Training Data.

Periklis Perikleous|Andreas Kafkalias|Zenonas Theodosiou|Pinar Barlas|Evgenia Christoforou|Jahna Otterbacher|Gianluca Demartini|Andreas Lanitis


Anthology ID:DBLP:conf/cikm/PerikleousKTBCO22
Volume:Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022
Year:2022
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:4951-4954
URL:https://doi.org/10.1145/3511808.3557178
DOI:https://doi.org/10.1145/3511808.3557178
DBLP:conf/cikm/PerikleousKTBCO22
BibTeX:
@inproceedings{perikleous-2022-crowd, author = {Periklis Perikleous and Andreas Kafkalias and Zenonas Theodosiou and Pinar Barlas and Evgenia Christoforou and Jahna Otterbacher and Gianluca Demartini and Andreas Lanitis}, editor = {Mohammad Al Hasan and Li Xiong}, title = {{How Does the Crowd Impact the Model? A Tool for Raising Awareness of Social Bias in Crowdsourced Training Data}}, booktitle = {{Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022}}, pages = {4951--4954}, publisher = {ACM}, year = {2022}, url = {https://doi.org/10.1145/3511808.3557178}, doi = {https://doi.org/10.1145/3511808.3557178} }