135 research outputs found
Constraints to supplemental tourism activities among Japanese outbound sport tourists : A case study of Japanese participants in the Asia Pacific Masters Games 2018 Penang
グラフ圧縮による媒介中心性の計算手法
本論文はグラフの各点の媒介中心性を求める計算手法を提案する.それは次数が1である点をグラフから除き,圧縮されたグラフで計算する.提案手法が,従来の手法の次数が1である点が存在するグラフで生じる冗長な計算を回避し,計算量を削減することを示す.This paper proposes a computation method to find a betweenness centrality of each vertex of a graph. The method compresses the original graph by removing vertices whose degree is one from the graph. The betweenness centrality is then calculated from the compressed graph. This avoids avoid blackundancy of the computation in the conventional method without the graph compression. As a result, the calculation time is blackuced
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
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