8 research outputs found
Annotation-Scheme Reconstruction for "Fake News" and Japanese Fake News Dataset
Fake news provokes many societal problems; therefore, there has been
extensive research on fake news detection tasks to counter it. Many fake news
datasets were constructed as resources to facilitate this task. Contemporary
research focuses almost exclusively on the factuality aspect of the news.
However, this aspect alone is insufficient to explain "fake news," which is a
complex phenomenon that involves a wide range of issues. To fully understand
the nature of each instance of fake news, it is important to observe it from
various perspectives, such as the intention of the false news disseminator, the
harmfulness of the news to our society, and the target of the news. We propose
a novel annotation scheme with fine-grained labeling based on detailed
investigations of existing fake news datasets to capture these various aspects
of fake news. Using the annotation scheme, we construct and publish the first
Japanese fake news dataset. The annotation scheme is expected to provide an
in-depth understanding of fake news. We plan to build datasets for both
Japanese and other languages using our scheme. Our Japanese dataset is
published at https://hkefka385.github.io/dataset/fakenews-japanese/.Comment: 13th International Conference on Language Resources and Evaluation
(LREC), 202
Root canal treatment of traumatized permanent teeth with external root resorption
External root resorption is an important challenge in the preservation of traumatized teeth. External root resorption is observed in cases of replanted teeth from dental trauma. Root canal dressing containing calcium hydroxide (Ca(OH)2) is one recommended clinical approach for external root resorption treatment. However, complete control of external resorption may not be possible due to certain factors, such as the smear layer, which is formed by reaming and filing during root canal treatments. The smear layer plugs dentinal tubules and inhibits the effects of Ca(OH)2 as a root canal dressing material. Our study showed that root canal irrigation with ethylenediaminetetraacetic acid (EDTA) and sodium hypochlorite (NaOCl) with an ultrasonic device is the most effective method to remove the smear layer. Additionally, we observed an alkaline environment at the outer root surface due to ion diffusion from Ca(OH)2 following this treatment. As a result, the combined use of EDTA and NaOCl with an ultrasonic device for root canal irrigation led to good control of external root resorption
Annotation-Scheme Reconstruction for “Fake News” and Japanese Fake News Dataset
Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), Marseille, 20-25 June 2022Fake news provokes many societal problems; therefore, there has been extensive research on fake news detection tasks to counter it. Many fake news datasets were constructed as resources to facilitate this task. Contemporary research focuses almost exclusively on the factuality aspect of the news. However, this aspect alone is insufficient to explain “fake news,” which is a complex phenomenon that involves a wide range of issues. To fully understand the nature of each instance of fake news, it is important to observe it from various perspectives, such as the intention of the false news disseminator, the
harmfulness of the news to our society, and the target of the news. We propose a novel annotation scheme with fine-grained labeling based on detailed investigations of existing fake news datasets to capture these various aspects of fake news. Using the annotation scheme, we construct and publish the first Japanese fake news dataset. The annotation scheme is expected to provide an in-depth understanding of fake news. We plan to build datasets for both Japanese and other languages using our scheme. Our Japanese dataset is published at https://hkefka385.github.io/dataset/fakenews-japanese/
Surveillance of early stage COVID-19 clusters using search query logs and mobile device-based location information
Two clusters of the coronavirus disease 2019 (COVID-19) were confirmed in Hokkaido, Japan, in February 2020. To identify these clusters, this study employed web search query logs of multiple devices and user location information from location-aware mobile devices. We anonymously identified users who used a web search engine (i.e., Yahoo! JAPAN) to search for COVID-19 or its symptoms. We regarded them as web searchers who were suspicious of their own COVID-19 infection (WSSCI). We extracted the location of WSSCI via a mobile operating system application and compared the spatio-temporal distribution of WSSCI with the actual location of the two known clusters. In the early stage of cluster development, we confirmed several WSSCI. Our approach was accurate in this stage and became biased after a public announcement of the cluster development. When other cluster-related resources, such as detailed population statistics, are not available, the proposed metric can capture hints of emerging clusters