Ensuring the Inclusive Use of Natural Language Processing in the Global Response to COVID-19

Abstract

Natural language processing (NLP) plays a significant role in tools for the COVID-19 pandemic response, from detecting misinformation on social media to helping to provide accurate clinical information or summarizing scientific research. However, the approaches developed thus far have not benefited all populations, regions or languages equally. We discuss ways in which current and future NLP approaches can be made more inclusive by covering lowresource languages, including alternative modalities, leveraging out-of-the-box tools and forming meaningful partnerships. We suggest several future directions for researchers interested in maximizing the positive societal impacts of NLP.

Agenda-Setting for COVID-19: A Study of Large-Scale Economic News Coverage Using Natural Language Processing

“…The need for a varied diet of content would be better met if researchers had quick access to condensed information compiled by a more objective approach. Therefore, NLP techniques have been widely used to mine COVID-19 related text data [30][31][32][33][34][35] belonging to different types, such as scientific literature [12,[36][37][38], social media posts from e.g., Sina Weibo [39][40][41], Reddit [42][43][44] and Twitter [40,[45][46][47][48][49][50][51][52][53][54][55][56][57][58], and news articles [59][60][61][62]. Many language comprehension tasks can be effectively solved with NLP, including information retrieval, misinformation detection, literature-based discovery, question answering, topic modeling and sentiment analysis [30,[63][64][65][66].…”