1 code implementation • WASSA (ACL) 2022 • Patrick John Ramos, Kiki Ferawati, Kongmeng Liew, Eiji Aramaki, Shoko Wakamiya
Afterwards, a correlation analysis between the extracted emotions and a set of vaccination measures in Japan was conducted. The results revealed that surprise and fear were the most intense emotions predicted by the model for writers and readers, respectively, on the vaccine-related Tweet dataset.
no code implementations • LREC 2022 • Taichi Murayama, Shohei Hisada, Makoto Uehara, Shoko Wakamiya, Eiji Aramaki
Using the annotation scheme, we construct and publish the first Japanese fake news dataset.
no code implementations • LREC 2022 • Fei Cheng, Shuntaro Yada, Ribeka Tanaka, Eiji Aramaki, Sadao Kurohashi
In this paper, we first propose a novel relation annotation schema for investigating the medical and temporal relations between medical entities in Japanese medical reports.
2 code implementations • 27 Mar 2024 • Lisa Raithel, Hui-Syuan Yeh, Shuntaro Yada, Cyril Grouin, Thomas Lavergne, Aurélie Névéol, Patrick Paroubek, Philippe Thomas, Tomohiro Nishiyama, Sebastian Möller, Eiji Aramaki, Yuji Matsumoto, Roland Roller, Pierre Zweigenbaum
User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world.
no code implementations • 6 Apr 2022 • Taichi Murayama, Shohei Hisada, Makoto Uehara, Shoko Wakamiya, Eiji Aramaki
Using the annotation scheme, we construct and publish the first Japanese fake news dataset.
1 code implementation • 8 Nov 2021 • Fei Cheng, Shuntaro Yada, Ribeka Tanaka, Eiji Aramaki, Sadao Kurohashi
We present an open-access natural language processing toolkit for Japanese medical information extraction.
no code implementations • WNUT (ACL) 2021 • Taichi Murayama, Shoko Wakamiya, Eiji Aramaki
Fake news causes significant damage to society. To deal with these fake news, several studies on building detection models and arranging datasets have been conducted.
no code implementations • 5 Jul 2021 • Taichi Murayama, Shoko Wakamiya, Eiji Aramaki
The accurate forecasting of infectious epidemic diseases such as influenza is a crucial task undertaken by medical institutions.
1 code implementation • 14 Jun 2021 • Shogo Ujiie, Hayate Iso, Eiji Aramaki
We introduce BioCoM, a contrastive learning framework for biomedical entity linking that uses only two resources: a small-sized dictionary and a large number of raw biomedical articles.
no code implementations • NAACL (BioNLP) 2021 • Shogo Ujiie, Hayate Iso, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
Disease name recognition and normalization, which is generally called biomedical entity linking, is a fundamental process in biomedical text mining.
1 code implementation • 31 Dec 2020 • Yuta Nakamura, Shouhei Hanaoka, Yukihiro Nomura, Naoto Hayashi, Osamu Abe, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
One problem is that previous studies have assessed the risk for different real-world privacy leakage scenarios and attack methods, which reduces the portability of the findings.
no code implementations • COLING 2020 • Zhiwei Gao, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
To make use of the similarity in offensive expressions among different social media platforms, we adopted state-of-the-art models trained on offensive expressions from Twitter for our Twitch data (i. e., transfer learning).
no code implementations • LREC 2020 • Shuntaro Yada, Ayami Joh, Ribeka Tanaka, Fei Cheng, Eiji Aramaki, Sadao Kurohashi
Applying natural language processing (NLP) to medical and clinical texts can bring important social benefits by mining valuable information from unstructured text.
no code implementations • 21 Apr 2020 • Shohei Hisada, Taichi Murayama, Kota Tsubouchi, Sumio Fujita, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
Second, we extracted the location of the WSSCI via the smartphone application.
1 code implementation • 17 Apr 2020 • Zhiwei Gao, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
This has affected the social life of people owing to enforcements, such as "social distancing" and "stay at home."
2 code implementations • ACL 2019 • Hayate Iso, Yui Uehara, Tatsuya Ishigaki, Hiroshi Noji, Eiji Aramaki, Ichiro Kobayashi, Yusuke Miyao, Naoaki Okazaki, Hiroya Takamura
We propose a data-to-text generation model with two modules, one for tracking and the other for text generation.
no code implementations • WS 2017 • Ryo Takeuchi, Hayate Iso, Kaoru Ito, Shoko Wakamiya, Eiji Aramaki
Based on these results, we can infer that social sensors can reliably detect unseasonal and local disease events under certain conditions, just as they can for seasonal or global events.
no code implementations • 8 May 2017 • Hayate Iso, Shoko Wakamiya, Eiji Aramaki
Nowadays, geographic information related to Twitter is crucially important for fine-grained applications.
no code implementations • WS 2016 • Daisaku Shibata, Shoko Wakamiya, Ayae Kinoshita, Eiji Aramaki
This study investigates features of the words that AD patients use in their spoken language.
no code implementations • WS 2016 • Eiji Aramaki, Yoshinobu Kano, Tomoko Ohkuma, Mizuki Morita
Due to the recent replacements of physical documents with electronic medical records (EMR), the importance of information processing in medical fields has been increased.
no code implementations • COLING 2016 • Hayate Iso, Shoko Wakamiya, Eiji Aramaki
Because of the increasing popularity of social media, much information has been shared on the internet, enabling social media users to understand various real world events.