Understanding the Pandemic Through Mining Covid News Using Natural Language Processing

Abstract

However, there is an insignificant number of NLP research invested in studying COVID-19. Most applications include the classification of chest X-rays and CT-scans to detect the presence of pneumonia in lungs [4], a consequence of the virus. Other research areas include studying the genome sequence of the virus [5] [6] [7] and replicating its structure to fight and find vaccines. Few NLP based research publications related to COVID-19 are sentiment classification of online tweets by Samuel et. al. [8] to understand fear persisting in people due to the virus. Similar work has been done using the LSTM network to classify sentiments from online discussion forums by Jelodar et. al. [9].Our research dives deeper with NLP to extract crucial information from newspaper reports regarding the virus and pandemic. At this stage, we considered all genres of news that are related to the virus. This collection of newspaper reports, we termed as "NNK Dataset", is the first study on a comparatively larger dataset of a newspaper report on COVID-19, which contributed to the virus's awareness to the best of our knowledge. The contribution of this paper includes:

Unleashing Competitive Intelligence: News Mining Analysis on Technology Trends and Digital Health Driving Healthcare Innovation

“…The goal was to generate competitive intelligence by identifying trends and integrating knowledge [57]. This section provides a clear overview of the study's precise procedures, whose steps were selecting the data source, preprocessing textual data, and utilizing NLP techniques such as named-entity extraction (NER), as in the research of the work in [69], relationship extraction [22], and clustering using graph-based models. Fig.…”

“…Despite the existing research on leveraging social media for healthcare insights, as detailed in our previous research on the use of social media analytics in healthcare [20], there are still significant gaps in the literature that require further research and the exploration of different data sources. Recent studies on news mining analysis in healthcare have focused mainly on the impact of COVID-19 and public health [21], [22], [23], and the impact of the digital transformation during the pandemic [24]. However, no studies have leveraged news mining to gain insights into healthcare businesses.…”

Public Perception Towards Children's COVID-19 Vaccination with Natural Language Processing

“…And also, Tang et al [42] showed the application of BERT for analyzing the tweets about the epidemic posted by health organizations. Sadman et al [43] collected news reports about the pandemic and used NLP techniques to obtain information about the number of cases, trending topics, emotions, and the virus. L. Li et al [10] received support from NLP techniques by processing the data pulled from the Weibo platform with the help of supervised learning to classify the available information about the epidemic into different types of situation information.…”

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].…”