A Multidimensional Dataset Based on Crowdsourcing for Analyzing and Detecting News Bias.

Michael Färber|Victoria Burkard|Adam Jatowt|Sora Lim


Anthology ID:DBLP:conf/cikm/0001BJL20
Volume:CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020
Year:2020
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:3007-3014
URL:https://doi.org/10.1145/3340531.3412876
DOI:https://doi.org/10.1145/3340531.3412876
DBLP:conf/cikm/0001BJL20
BibTeX:
@inproceedings{farber-2020-multidimensional, author = {Michael F\"{a}rber and Victoria Burkard and Adam Jatowt and Sora Lim}, editor = {Mathieu d'Aquin and Stefan Dietze and Claudia Hauff and Edward Curry and Philippe Cudr\'{e}-Mauroux}, title = {{A Multidimensional Dataset Based on Crowdsourcing for Analyzing and Detecting News Bias}}, booktitle = {{CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020}}, pages = {3007--3014}, publisher = {ACM}, year = {2020}, url = {https://doi.org/10.1145/3340531.3412876}, doi = {https://doi.org/10.1145/3340531.3412876} }