In this section
@inproceedings{Kotonya:2020:v1/2020.coling-main.474,
author = {Kotonya, N and Toni, F},
doi = {v1/2020.coling-main.474},
pages = {5430--5443},
publisher = {International Committee on Computational Linguistics},
title = {Explainable Automated Fact-Checking: A Survey},
url = {http://dx.doi.org/10.18653/v1/2020.coling-main.474},
year = {2020}
}
TY - CPAPER
AB - A number of exciting advances have been made in automated fact-checkingthanks to increasingly larger datasets and more powerful systems, leading toimprovements in the complexity of claims which can be accurately fact-checked.However, despite these advances, there are still desirable functionalitiesmissing from the fact-checking pipeline. In this survey, we focus on theexplanation functionality -- that is fact-checking systems providing reasonsfor their predictions. We summarize existing methods for explaining thepredictions of fact-checking systems and we explore trends in this topic.Further, we consider what makes for good explanations in this specific domainthrough a comparative analysis of existing fact-checking explanations againstsome desirable properties. Finally, we propose further research directions forgenerating fact-checking explanations, and describe how these may lead toimprovements in the research area.v
AU - Kotonya,N
AU - Toni,F
DO - v1/2020.coling-main.474
EP - 5443
PB - International Committee on Computational Linguistics
PY - 2020///
SP - 5430
TI - Explainable Automated Fact-Checking: A Survey
UR - http://dx.doi.org/10.18653/v1/2020.coling-main.474
UR - https://www.aclweb.org/anthology/2020.coling-main.474/
UR - http://hdl.handle.net/10044/1/86212
ER -
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