Spatial Sentiment and Perception Analysis of BBC News Articles Using Twitter Posts Mining

Younas, Farah; Owda, Majdi

doi:10.1007/978-3-030-55187-2_27

Cited by 3 publications

(2 citation statements)

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“…These positive changes in news articles could affect the reader’s perception. 63 In other words, it could influence the public reading the article to have a positive perception of telemedicine. Also, a positive change in the tone of a news article could affect public preference for telemedicine.…”

Section: Discussionmentioning

confidence: 99%

Contents and sentiment analysis of newspaper articles and comments on telemedicine in Korea: Before and after of COVID-19 outbreak

Kang

Song

2022

Health Informatics J

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Telemedicine is rapidly growing to meet the increased needs for high-quality health care during the COVID-19 pandemic. However, telemedicine is still a sensitive issue as it is related to medical privatization. The use of telemedicine after the COVID-19 outbreak might be influenced by public opinion, and this may be an important key in implementing telemedicine. In this study, we aimed to assess if telemedicine-related newspaper articles and comments changed positively during the COVID-19 pandemic. From January 1, 2019, to March 1, 2020 (before COVID-19), a total of 1073 telemedicine-related articles were found in the Korean news network. Although the post-COVID-19 article collection period (from March 2, 2020, to September 30, 2020) was about half that of the pre-COVID-19, about twice the number (1934) of telemedicine-related articles were collected. And telemedicine-related news articles had a more positive tone post-COVID-19 than pre-COVID-19 (52.9% after vs 40.4% before). In conclusion, this study presented the association between the COVID-19 outbreak and changes in the media’s perception of telemedicine in Korea. This study presented that, as telemedicine begins to be utilized due to COVID-19, news media and readers who embrace it are beginning to view telemedicine positively, suggesting that COVID-19 has a positive foundation for the spread of telemedicine.

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Section: Discussionmentioning

confidence: 99%

Contents and sentiment analysis of newspaper articles and comments on telemedicine in Korea: Before and after of COVID-19 outbreak

Kang

Song

2022

Health Informatics J

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“…В работе [3] автор предложил алгоритм, позволяющий узнать общественное мнение граждан Индии о налоговой системе, одобренной правительством Индии, поскольку из Twitter было собрано 190 твитов о налоговой системе на английском языке, а затем применен лексический подход для определения чувств, которые каждый твит несет. В работе [4] автор предложил лексический подход для добычи неструктурированных данных из Twitter, чтобы установить семантическую тенденцию взаимодействий и мнений в режиме реального времени путем извлечения настроений аудитории из комментариев, связанных с новостными статьями BBC, публикуемыми в Twitter.…”

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Analysis of Public Reaction to E-Learning on Twitter

A.-R.¹,

K.A.²

2022

RR. I.T.

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Over the past few decades, due to the explosive growth of social media, online resources, and microblogging sites such as Twitter. There was an influx of user-generated content. The data obtained from these resources is a rich source of information for data mining. Sentiment analysis is a current and important area of research that attempts to determine the polarity of a text. The definition of feelings about current events in the world has become crucial. This article focuses on data mining on Twitter and defining opinions regarding e-learning. The focus is on identifying sentiment from e-learning-related texts that are shared on Twitter. About 3,000 tweets were extracted and the polarity of those tweets was detected, and then visualize the resulting data.

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Automatic Monitoring and Analysis of Brands Using Data Extracted from Twitter in Romanian

Istrati¹,

Ciobotaru²

2021

Lecture Notes in Networks and Systems

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Spatial Sentiment and Perception Analysis of BBC News Articles Using Twitter Posts Mining

Cited by 3 publications

References 9 publications

Contents and sentiment analysis of newspaper articles and comments on telemedicine in Korea: Before and after of COVID-19 outbreak

Contents and sentiment analysis of newspaper articles and comments on telemedicine in Korea: Before and after of COVID-19 outbreak

Analysis of Public Reaction to E-Learning on Twitter

Automatic Monitoring and Analysis of Brands Using Data Extracted from Twitter in Romanian

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