Understanding COVID-19 News Coverage using Medical NLP

Varol, Ali Emre; Kocaman, Veysel; Haq, Hasham Ul; Talby, David

doi:10.48550/arxiv.2203.10338

Cited by 5 publications

(5 citation statements)

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“…The significance and contribution of this study to data science lies mainly in the novel application of a set of advanced NLP techniques to retrieve key information from long news article texts. The proposal of this analysis framework goes beyond existing research that either trains only an embedding model based on news [104] or directly uses the existing models from Spark NLP to analyze them [105]. Instead of the traditional Word2Vec embedding and LDA-based topic modeling methods [106], our analytical approach is based on the state-of-the-art sentence embedding techniques Sentence-BERT and the density-based clustering algorithm Top2Vec, which attempt to encode all textual information into different economic topics as defined by the WEF.…”

Section: Discussion and Contributionmentioning

confidence: 99%

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

Businger

Dollfus

et al. 2022

Int J Data Sci Anal

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Over the past two years, organizations and businesses have been forced to constantly adapt and develop effective responses to the challenges of the COVID-19 pandemic. The acuteness, global scale and intense dynamism of the situation make online news and information even more important for making informed management and policy decisions. This paper focuses on the economic impact of the COVID-19 pandemic, using natural language processing (NLP) techniques to examine the news media as the main source of information and agenda-setters of public discourse over an eight-month period. The aim of this study is to understand which economic topics news media focused on alongside the dominant health coverage, which topics did not surface, and how these topics influenced each other and evolved over time and space. To this end, we used an extensive open-source dataset of over 350,000 media articles on non-medical aspects of COVID-19 retrieved from over 60 top-tier business blogs and news sites. We referred to the World Economic Forum’s Strategic Intelligence taxonomy to categorize the articles into a variety of topics. In doing so, we found that in the early days of COVID-19, the news media focused predominantly on reporting new cases, which tended to overshadow other topics, such as the economic impact of the virus. Different independent news sources reported on the same topics, showing a herd behavior of the news media during this global health crisis. However, a temporal analysis of news distribution in relation to its geographic focus showed that the rise in COVID-19 cases was associated with an increase in media coverage of relevant socio-economic topics. This research helps prepare for the prevention of social and economic crises when decision-makers closely monitor news coverage of viruses and related topics in other parts of the world. Thus, monitoring the news landscape on a global scale can support decision-making in social and economic crises. Our analyses point to ways in which this monitoring and issues management can be improved to remain alert to social dynamics and market changes.

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Section: Discussion and Contributionmentioning

confidence: 99%

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

Businger

Dollfus

et al. 2022

Int J Data Sci Anal

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“…Natural language processing (NLP) has recently gained much attention due to its potential to accurately represent and interpret human language using computers [28]. Machine translation [29], detecting spamming mail [30], extracting information [31], as well as in medicine in recent times, such as Covid [32] are just some of the many applications it has found success in recently. Successors to the BERT (Bidirectional Encoder Representations from Transformers) method have also proven beneficial for NLP [33].…”

Section: A State Of Nlp Research In Fake News Detectionmentioning

confidence: 99%

Toward News Authenticity: Synthesizing Natural Language Processing and Human Expert Opinion to Evaluate News

et al. 2023

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The growing popularity of online news has prompted concerns regarding (i) the socio-political influence over news dissemination, (ii) the waning freedom of news media, (iii) and a facile news evaluation process. A piece of news having the power to capture a large audience and sow the seed of bizarre consequences on a national scale should be prudently evaluated before reaching the mass. In quest of making a substantial profit, and sometimes due to inevitable socio-political influence, news with biased heading outpours mass media, resulting in ambiguity and mass manipulation. In this paper, we suggest a blockchain, smart contract, and incremental machine learning-based news evaluation procedure for the Bengali language to overcome these challenges. Weighted synthesis of machine classification and human expert opinion in a decentralized platform are synthesized to evaluate news. With continuous data, the Natural Language Processing (NLP) model is incrementally trained, and the best version of the model is used to detect deprived fake news. During experiments, the NLP model with initial training and testing accuracy of 84.94% and 84.99% was increased to 93.75% and 93.80% after nine rounds of incremental model training. On the Ethereum test network, the protocols have been installed and tested. The simulation demonstrates successful implementation of our proposed system.

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“…The phenomenon of vaccination has been studied from different perspectives, especially the one of public health [35], but there is also a considerable number of studies that investigate it from a media perspective [36]. The analysis of news coverage of the vaccination issue during COVID-19 pandemic aroused the interest of the scientific community [37], which also approached it from the position of data analysis in order to gain insight and allow more efficient interpretation [38].…”

Section: Related Researchmentioning

confidence: 99%

“…In order to perform the analysis of post headlines, initially it was necessary to determine the sources from which the data collection would be carried out. Given that analysis is focused on news portals in Croatia, the Reuters Institute Digital News Reports [38] of online brands was used as a criteria for their selection. These reports are published by Reuters Institute for the Study of Journalism (RISJ) on an annual basis and provide key indicators for various news media.…”

Section: A Data Source Selectionmentioning

confidence: 99%

Data Analysis of the Web News Headlines based on Natural Language Processing

Karna

Braović

Vickovic

et al. 2023

JCOMSS

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This paper explores the problem of media content data analysis with the focus on the phenomenon of vaccination, closely related to the COVID-19 pandemic. The presented research is an extension of the previous work, but it differs in two main areas. Firstly, the text corpus submitted to the analysis has been considerably increased. Secondly, the previous data analysis was performed on the body part of the posts, while now it is focused on the most prominent part of the news posts, their headlines. This change from body to headline analysis was provoked by significant differences in their characteristics and the fact that most people read only headlines. Described data acquisition uses an advanced content collection approach followed by the modeling process, during which a set of natural language processing algorithms were applied. To enable the comparison, the model uses the same set of algorithms in the modeling phase like in previous work. The main contributions of the work are manifested in: i) approaching the problem from a new perspective, ii) applying more efficient method of data collection, and crucially iii) enabling the comparison of analysis results for individual parts of the content, which ensured a comprehensive insight into the characteristics of news posts.

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Understanding COVID-19 News Coverage using Medical NLP

Cited by 5 publications

References 0 publications

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

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

Toward News Authenticity: Synthesizing Natural Language Processing and Human Expert Opinion to Evaluate News

Data Analysis of the Web News Headlines based on Natural Language Processing

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