The Content Analysis of Social Media Shares in Turkish Related to COVID-19

A remarkable increase has currently been happening in social media platform content related to COVID-19. Users have created large volumes of content on various topics over a short time, interacting with people in real-time. This also has transformed social media into an indispensable information sou...

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Main Author: M. Fevzi Esen
Format: Article
Language:English
Published: İlmi Etüdler Derneği 2021-09-01
Series:İnsan & Toplum
Subjects:
Online Access:https://insanvetoplum.org/content/6-sayilar/29-11-3/m0629/esen.pdf
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spelling doaj-b249d0103b19408ea0bdc54bbc7cd46c2021-09-16T12:21:58Zengİlmi Etüdler Derneğiİnsan & Toplum2146-70992602-27452021-09-01113113137dx.doi.org/10.12658/M0629The Content Analysis of Social Media Shares in Turkish Related to COVID-19M. Fevzi Esen0https://orcid.org/0000-0001-7823-0883University of Health SciencesA remarkable increase has currently been happening in social media platform content related to COVID-19. Users have created large volumes of content on various topics over a short time, interacting with people in real-time. This also has transformed social media into an indispensable information source for any crisis. This study aims to explore the information content on COVID-19 disseminated through social media and to discover prominent topics in shares on COVID-19. In this regard, we have retrieved 17,542 tweets shared in Turkish. A content analysis of social media shares has been carried out, with latent semantic indexing and network analyses being performed to detect the relationships and interactions among shares. As a result, the most shared topics have been concluded to be on yasak [lockdown], tedbir [precaution], karantina [quarantine], and vaka [case], with communication being frequently passed using this semantic string and information exchanges being faster within the network. In addition, shares related to hygiene, masks, and distancing were determined to have occurred less than shares related to precautions, rules, cases, and lockdowns. The number of likes and retweets for content with social propaganda such as #evdekal [stayathome], #evdehayatvar [lifeathome], and #birliktebaşaracağız [togetherwesucceed] were low and not found in a semantic string. This suggests social propaganda through social media to have had a limited impact on epidemic management. In conclusion, identifying the prominent issues in social media posts and the characteristics of social media networks will help decision-makers determine appropriate policies for controlling and preventing the pandemic’s spread.https://insanvetoplum.org/content/6-sayilar/29-11-3/m0629/esen.pdf: covid-19social media analysistext miningsocial propagandacontent analysis
collection DOAJ
language English
format Article
sources DOAJ
author M. Fevzi Esen
spellingShingle M. Fevzi Esen
The Content Analysis of Social Media Shares in Turkish Related to COVID-19
İnsan & Toplum
: covid-19
social media analysis
text mining
social propaganda
content analysis
author_facet M. Fevzi Esen
author_sort M. Fevzi Esen
title The Content Analysis of Social Media Shares in Turkish Related to COVID-19
title_short The Content Analysis of Social Media Shares in Turkish Related to COVID-19
title_full The Content Analysis of Social Media Shares in Turkish Related to COVID-19
title_fullStr The Content Analysis of Social Media Shares in Turkish Related to COVID-19
title_full_unstemmed The Content Analysis of Social Media Shares in Turkish Related to COVID-19
title_sort content analysis of social media shares in turkish related to covid-19
publisher İlmi Etüdler Derneği
series İnsan & Toplum
issn 2146-7099
2602-2745
publishDate 2021-09-01
description A remarkable increase has currently been happening in social media platform content related to COVID-19. Users have created large volumes of content on various topics over a short time, interacting with people in real-time. This also has transformed social media into an indispensable information source for any crisis. This study aims to explore the information content on COVID-19 disseminated through social media and to discover prominent topics in shares on COVID-19. In this regard, we have retrieved 17,542 tweets shared in Turkish. A content analysis of social media shares has been carried out, with latent semantic indexing and network analyses being performed to detect the relationships and interactions among shares. As a result, the most shared topics have been concluded to be on yasak [lockdown], tedbir [precaution], karantina [quarantine], and vaka [case], with communication being frequently passed using this semantic string and information exchanges being faster within the network. In addition, shares related to hygiene, masks, and distancing were determined to have occurred less than shares related to precautions, rules, cases, and lockdowns. The number of likes and retweets for content with social propaganda such as #evdekal [stayathome], #evdehayatvar [lifeathome], and #birliktebaşaracağız [togetherwesucceed] were low and not found in a semantic string. This suggests social propaganda through social media to have had a limited impact on epidemic management. In conclusion, identifying the prominent issues in social media posts and the characteristics of social media networks will help decision-makers determine appropriate policies for controlling and preventing the pandemic’s spread.
topic : covid-19
social media analysis
text mining
social propaganda
content analysis
url https://insanvetoplum.org/content/6-sayilar/29-11-3/m0629/esen.pdf
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