Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020最新文献

Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media 荷兰社交媒体上民众对政府新冠疫情应对措施的看法

Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 Pub Date : 2020-09-03 DOI: 10.18653/V1/2020.NLPCOVID19-2.17

Shihan Wang, M. Schraagen, E. T. K. Sang, M. Dastani

引用次数: 16

COVID-19: A Semantic-Based Pipeline for Recommending Biomedical Entities COVID-19:基于语义的生物医学实体推荐管道

Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 Pub Date : 2020-09-03 DOI: 10.18653/v1/2020.nlpcovid19-2.20

Márcia Barros, Andre Lamurias, Diana Sousa, Pedro Ruas, Francisco M. Couto

{"title":"COVID-19: A Semantic-Based Pipeline for Recommending Biomedical Entities","authors":"Márcia Barros, Andre Lamurias, Diana Sousa, Pedro Ruas, Francisco M. Couto","doi":"10.18653/v1/2020.nlpcovid19-2.20","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcovid19-2.20","url":null,"abstract":"With the increasing number of publications about COVID-19, it is a challenge to extract personalized knowledge suitable for each researcher. This work aims to build a new semantic-based pipeline for recommending biomedical entities to scientific researchers. To this end, we developed a pipeline that creates an implicit feedback matrix based on Named Entity Recognition (NER) on a corpus of documents, using multidisciplinary ontologies for recognizing and linking the entities. Our hypothesis is that by using ontologies from different fields in the NER phase, we can improve the results for state-of-the-art collaborative-filtering recommender systems applied to the dataset created. The tests performed using the COVID-19 Open Research Dataset (CORD-19) dataset show that when using four ontologies, the results for precision@k, for example, reach the 80%, whereas when using only one ontology, the results for precision@k drops to 20%, for the same users. Furthermore, the use of multi-fields entities may help in the discovery of new items, even if the researchers do not have items from that field in their set of preferences.","PeriodicalId":131251,"journal":{"name":"Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132098672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Developing a Curated Topic Model for COVID-19 Medical Research Literature 建立COVID-19医学研究文献的策划主题模型

Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 Pub Date : 2020-08-12 DOI: 10.18653/v1/2020.nlpcovid19-2.30

P. Resnik, K. Goodman, Mike Moran

引用次数: 5

Characterizing drug mentions in COVID-19 Twitter Chatter 在COVID-19推特聊天中提到的药物特征

Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 Pub Date : 2020-07-20 DOI: 10.18653/v1/2020.nlpcovid19-2.25

Ramya Tekumalla, J. Banda

引用次数: 9

CAiRE-COVID: A Question Answering and Query-focused Multi-Document Summarization System for COVID-19 Scholarly Information Management cire - covid:面向新型冠状病毒学术信息管理的问答查询多文献汇总系统

Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 Pub Date : 2020-05-04 DOI: 10.18653/v1/2020.nlpcovid19-2.14

Dan Su, Yan Xu, Tiezheng Yu, Farhad Bin Siddique, Elham J. Barezi, Pascale Fung

{"title":"CAiRE-COVID: A Question Answering and Query-focused Multi-Document Summarization System for COVID-19 Scholarly Information Management","authors":"Dan Su, Yan Xu, Tiezheng Yu, Farhad Bin Siddique, Elham J. Barezi, Pascale Fung","doi":"10.18653/v1/2020.nlpcovid19-2.14","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcovid19-2.14","url":null,"abstract":"The outbreak of COVID-19 raises attention from the researchers from various communities. While many scientific articles have been published, a system that can provide reliable information to COVID-19 related questions from the latest academic resources is crucial, especially for the medical community in the current time-critical race to treat patients and to find a cure for the virus. To address the requests, we propose our CAiRE-COVID, a neural-based system that uses open-domain question answering (QA) techniques combined with summarization techniques for mining the available scientific literature. It leverages the Information Retrieval (IR) system and QA models to extract relevant snippets from existing literature given a query. Fluent summaries are also provided to help understand the content in a more efficient way. Our system has been awarded as winner for one of the tasks in CORD-19 Kaggle Challenge. We also launched our CAiRE-COVID website for broader use. The code for our system is also open-sourced to bootstrap further study.","PeriodicalId":131251,"journal":{"name":"Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116835478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 75

Tracking And Understanding Public Reaction During COVID-19: Saudi Arabia As A Use Case 跟踪和了解COVID-19期间的公众反应:以沙特阿拉伯为例

Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 Pub Date : 1900-01-01 DOI: 10.18653/v1/2020.nlpcovid19-2.24

Aseel Addawood, Alhanouf Alsuwailem, Ali Alohali, D. Alajaji, Mashail Alturki, Jaida Alsuhaibani, Fawziah Aljabli

{"title":"Tracking And Understanding Public Reaction During COVID-19: Saudi Arabia As A Use Case","authors":"Aseel Addawood, Alhanouf Alsuwailem, Ali Alohali, D. Alajaji, Mashail Alturki, Jaida Alsuhaibani, Fawziah Aljabli","doi":"10.18653/v1/2020.nlpcovid19-2.24","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcovid19-2.24","url":null,"abstract":"The coronavirus disease of 2019 (COVID-19) has had a huge impact on economies and societies around the world. While governments are taking extreme measures to reduce the spread of the virus, people are being affected by these new measures. With restrictions like lockdowns and social distancing, it has become important to understand the emotional response of the public towards the pandemic. In this paper, we study the reaction of Saudi Arabian citizens towards the pandemic. We utilize a collection of Arabic tweets that were sent during 2020, primarily through hashtags that originated in Saudi Arabia. Our results showed that people had maintained a positive reaction towards the pandemic. This positive reaction was at its highest at the beginning of the COVID-19 crisis and started to decline as time passed. Overall, the results showed that people were highly supportive of each other through this pandemic. This research can help researchers and policymakers in understanding the emotional effect of a pandemic on societies.","PeriodicalId":131251,"journal":{"name":"Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127449895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Improved Topic Representations of Medical Documents to Assist COVID-19 Literature Exploration 改进医学文献主题表示，辅助COVID-19文献检索

Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 Pub Date : 1900-01-01 DOI: 10.18653/v1/2020.nlpcovid19-2.12

Yulia Otmakhova, K. Verspoor, Timothy Baldwin, Simon Suster, Jey Han Lau

引用次数: 5

Explaining the Trump Gap in Social Distancing Using COVID Discourse 用COVID话语解释社交距离中的特朗普差距

Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020 Pub Date : 1900-01-01 DOI: 10.18653/v1/2020.nlpcovid19-2.10

Austin Van Loon, Sheridan A Stewart, Brandon Waldon, S. K. Lakshmikanth, Ishan Shah, Sharath Chandra Guntuku, G. Sherman, J. Zou, J. Eichstaedt

{"title":"Explaining the Trump Gap in Social Distancing Using COVID Discourse","authors":"Austin Van Loon, Sheridan A Stewart, Brandon Waldon, S. K. Lakshmikanth, Ishan Shah, Sharath Chandra Guntuku, G. Sherman, J. Zou, J. Eichstaedt","doi":"10.18653/v1/2020.nlpcovid19-2.10","DOIUrl":"https://doi.org/10.18653/v1/2020.nlpcovid19-2.10","url":null,"abstract":"Our ability to limit the future spread of COVID-19 will in part depend on our understanding of the psychological and sociological processes that lead people to follow or reject coronavirus health behaviors. We argue that the virus has taken on heterogeneous meanings in communities across the United States and that these disparate meanings shaped communities’ response to the virus during the early, vital stages of the outbreak in the U.S. Using word embeddings, we demonstrate that counties where residents socially distanced less on average (as measured by residential mobility) more semantically associated the virus in their COVID discourse with concepts of fraud, the political left, and more benign illnesses like the flu. We also show that the different meanings the virus took on in different communities explains a substantial fraction of what we call the “Trump Gap,” or the empirical tendency for more Trump-supporting counties to socially distance less. This work demonstrates that community-level processes of meaningmaking determined behavioral responses to the COVID-19 pandemic and that these processes can be measured unobtrusively using Twitter.","PeriodicalId":131251,"journal":{"name":"Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020","volume":"914 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132793212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8