Analysis of Covid-19 News Using Text Mining Techniques

Emine Çağatay; Bahar Y. Sünnetci; Selin Orbay; Tolga Kaya

doi:10.1007/978-3-031-09176-6_50

Analysis of Covid-19 News Using Text Mining Techniques

Emine Çağatay^*
, Bahar Y. Sünnetci
, Selin Orbay
, Tolga Kaya

^*Corresponding author for this work

Department of Management Engineering

Istanbul Technical University
Hisar School

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

COVID-19, which has taken the whole world under its influence, has been a remarkable period to investigate the emotions and behaviors of people in extraordinary situations. The findings addressed during this defining moment to the fluctuation of the number of cases and certain turning points. It is a matter of debate how much these important moments are affected by the attitudes of the authorities directing the public. The aim of this study is to determine in which periods and what expressions the news in the newspapers is used by using text mining techniques such as word clouds, clustering and sentiment analysis. In order to do this, COVID-19 news published in the last two years from three respected newspapers were used. Results reveal that, there are significant changes in the main themes of the COVID-19 related news with the release of the vaccine. Moreover, when all periods are inspected, it has been observed that different topics like herd immunity, vaccination, variants and human rights have come to the forefront in various print media sources.

Original language	English
Title of host publication	Intelligent and Fuzzy Systems - Digital Acceleration and The New Normal - Proceedings of the INFUS 2022 Conference, Volume 2
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, A. Cagri Tolga, Selcuk Cebi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	438-445
Number of pages	8
ISBN (Print)	9783031091759
DOIs	https://doi.org/10.1007/978-3-031-09176-6_50
Publication status	Published - 2022
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2022 - Izmir, Turkey Duration: 19 Jul 2022 → 21 Jul 2022

Publication series

Name	Lecture Notes in Networks and Systems
Volume	505 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2022
Country/Territory	Turkey
City	Izmir
Period	19/07/22 → 21/07/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 16 Peace, Justice and Strong Institutions

Keywords

COVID-19
Clustering
Coronavirus
Sentiment analysis
Text mining
Vaccination

Access to Document

10.1007/978-3-031-09176-6_50

Cite this

Çağatay, E., Sünnetci, B. Y., Orbay, S., & Kaya, T. (2022). Analysis of Covid-19 News Using Text Mining Techniques. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, A. C. Tolga, & S. Cebi (Eds.), Intelligent and Fuzzy Systems - Digital Acceleration and The New Normal - Proceedings of the INFUS 2022 Conference, Volume 2 (pp. 438-445). (Lecture Notes in Networks and Systems; Vol. 505 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-09176-6_50

Çağatay, Emine ; Sünnetci, Bahar Y. ; Orbay, Selin et al. / Analysis of Covid-19 News Using Text Mining Techniques. Intelligent and Fuzzy Systems - Digital Acceleration and The New Normal - Proceedings of the INFUS 2022 Conference, Volume 2. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; A. Cagri Tolga ; Selcuk Cebi. Springer Science and Business Media Deutschland GmbH, 2022. pp. 438-445 (Lecture Notes in Networks and Systems).

@inproceedings{52cd21c7f1474e0397c0fa2c9db3fad1,

title = "Analysis of Covid-19 News Using Text Mining Techniques",

abstract = "COVID-19, which has taken the whole world under its influence, has been a remarkable period to investigate the emotions and behaviors of people in extraordinary situations. The findings addressed during this defining moment to the fluctuation of the number of cases and certain turning points. It is a matter of debate how much these important moments are affected by the attitudes of the authorities directing the public. The aim of this study is to determine in which periods and what expressions the news in the newspapers is used by using text mining techniques such as word clouds, clustering and sentiment analysis. In order to do this, COVID-19 news published in the last two years from three respected newspapers were used. Results reveal that, there are significant changes in the main themes of the COVID-19 related news with the release of the vaccine. Moreover, when all periods are inspected, it has been observed that different topics like herd immunity, vaccination, variants and human rights have come to the forefront in various print media sources.",

keywords = "COVID-19, Clustering, Coronavirus, Sentiment analysis, Text mining, Vaccination",

author = "Emine {\c C}ağatay and S{\"u}nnetci, \{Bahar Y.\} and Selin Orbay and Tolga Kaya",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2022 ; Conference date: 19-07-2022 Through 21-07-2022",

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Çağatay, E, Sünnetci, BY, Orbay, S & Kaya, T 2022, Analysis of Covid-19 News Using Text Mining Techniques. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, AC Tolga & S Cebi (eds), Intelligent and Fuzzy Systems - Digital Acceleration and The New Normal - Proceedings of the INFUS 2022 Conference, Volume 2. Lecture Notes in Networks and Systems, vol. 505 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 438-445, International Conference on Intelligent and Fuzzy Systems, INFUS 2022, Izmir, Turkey, 19/07/22. https://doi.org/10.1007/978-3-031-09176-6_50

Analysis of Covid-19 News Using Text Mining Techniques. / Çağatay, Emine; Sünnetci, Bahar Y.; Orbay, Selin et al.
Intelligent and Fuzzy Systems - Digital Acceleration and The New Normal - Proceedings of the INFUS 2022 Conference, Volume 2. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; A. Cagri Tolga; Selcuk Cebi. Springer Science and Business Media Deutschland GmbH, 2022. p. 438-445 (Lecture Notes in Networks and Systems; Vol. 505 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Analysis of Covid-19 News Using Text Mining Techniques

AU - Çağatay, Emine

AU - Sünnetci, Bahar Y.

AU - Orbay, Selin

AU - Kaya, Tolga

PY - 2022

Y1 - 2022

N2 - COVID-19, which has taken the whole world under its influence, has been a remarkable period to investigate the emotions and behaviors of people in extraordinary situations. The findings addressed during this defining moment to the fluctuation of the number of cases and certain turning points. It is a matter of debate how much these important moments are affected by the attitudes of the authorities directing the public. The aim of this study is to determine in which periods and what expressions the news in the newspapers is used by using text mining techniques such as word clouds, clustering and sentiment analysis. In order to do this, COVID-19 news published in the last two years from three respected newspapers were used. Results reveal that, there are significant changes in the main themes of the COVID-19 related news with the release of the vaccine. Moreover, when all periods are inspected, it has been observed that different topics like herd immunity, vaccination, variants and human rights have come to the forefront in various print media sources.

AB - COVID-19, which has taken the whole world under its influence, has been a remarkable period to investigate the emotions and behaviors of people in extraordinary situations. The findings addressed during this defining moment to the fluctuation of the number of cases and certain turning points. It is a matter of debate how much these important moments are affected by the attitudes of the authorities directing the public. The aim of this study is to determine in which periods and what expressions the news in the newspapers is used by using text mining techniques such as word clouds, clustering and sentiment analysis. In order to do this, COVID-19 news published in the last two years from three respected newspapers were used. Results reveal that, there are significant changes in the main themes of the COVID-19 related news with the release of the vaccine. Moreover, when all periods are inspected, it has been observed that different topics like herd immunity, vaccination, variants and human rights have come to the forefront in various print media sources.

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KW - Coronavirus

KW - Sentiment analysis

KW - Text mining

KW - Vaccination

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AN - SCOPUS:85135057695

SN - 9783031091759

T3 - Lecture Notes in Networks and Systems

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BT - Intelligent and Fuzzy Systems - Digital Acceleration and The New Normal - Proceedings of the INFUS 2022 Conference, Volume 2

A2 - Kahraman, Cengiz

A2 - Cevik Onar, Sezi

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A2 - Sari, Irem Ucal

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PB - Springer Science and Business Media Deutschland GmbH

T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2022

Y2 - 19 July 2022 through 21 July 2022

ER -

Çağatay E, Sünnetci BY, Orbay S, Kaya T. Analysis of Covid-19 News Using Text Mining Techniques. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Tolga AC, Cebi S, editors, Intelligent and Fuzzy Systems - Digital Acceleration and The New Normal - Proceedings of the INFUS 2022 Conference, Volume 2. Springer Science and Business Media Deutschland GmbH. 2022. p. 438-445. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-09176-6_50

Analysis of Covid-19 News Using Text Mining Techniques

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this