Syeda Hina Batool, W. Ahmed, K. Mahmood, Ashraf Sharif
{"title":"COVID-19期间巴基斯坦Twitter数据的社交网络分析","authors":"Syeda Hina Batool, W. Ahmed, K. Mahmood, Ashraf Sharif","doi":"10.1108/idd-03-2021-0022","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe use of social media has increased during the COVID-19 pandemic. Social media platforms provide opportunities to share news, ideas and personal stories. Twitter is used by citizens in Pakistan to respond and comment on emerging news stories and events. However, it is not known whether Twitter played a positive or negative role in spreading updates and preventive messages during the COVID-19 pandemic. The purpose of this study is to analyse content from Twitter during the pandemic.\n\n\nDesign/methodology/approach\nNodeXL was used to retrieve data using the keyword وائرس کورونا (written in Urdu and which translates to Coronavirus). The first data set (Case Study 1) was based on 10,284 Twitter users from the end of March. The second data set (Case Study 2) was based on 10,644 Twitter users from the start of April. The theoretical lens of effective message framing was used to classify the most retweeted content on Twitter.\n\n\nFindings\nTwitter was used for personal and professional projections and included certain tweets included political motives even during the unfolding health crisis. There appeared to be very few successful attempts to use Twitter as a tool for health awareness and risk communication. The empirical findings indicate that the most retweeted messages were gain-framed and can be classified as personal, informative and political in nature.\n\n\nOriginality/value\nThe present study provides insights likely to be of interest to researchers, health organizations, citizens, government and politicians that are interested in making more effective use of social media for the purposes of health promotion. The authors also provide novel insights into the key topics of discussions, websites and hashtags used by Pakistani Twitter users during the COVID-19 pandemic.\n","PeriodicalId":43488,"journal":{"name":"Information Discovery and Delivery","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Social network analysis of Twitter data from Pakistan during COVID-19\",\"authors\":\"Syeda Hina Batool, W. Ahmed, K. Mahmood, Ashraf Sharif\",\"doi\":\"10.1108/idd-03-2021-0022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe use of social media has increased during the COVID-19 pandemic. Social media platforms provide opportunities to share news, ideas and personal stories. Twitter is used by citizens in Pakistan to respond and comment on emerging news stories and events. However, it is not known whether Twitter played a positive or negative role in spreading updates and preventive messages during the COVID-19 pandemic. The purpose of this study is to analyse content from Twitter during the pandemic.\\n\\n\\nDesign/methodology/approach\\nNodeXL was used to retrieve data using the keyword وائرس کورونا (written in Urdu and which translates to Coronavirus). The first data set (Case Study 1) was based on 10,284 Twitter users from the end of March. The second data set (Case Study 2) was based on 10,644 Twitter users from the start of April. The theoretical lens of effective message framing was used to classify the most retweeted content on Twitter.\\n\\n\\nFindings\\nTwitter was used for personal and professional projections and included certain tweets included political motives even during the unfolding health crisis. There appeared to be very few successful attempts to use Twitter as a tool for health awareness and risk communication. The empirical findings indicate that the most retweeted messages were gain-framed and can be classified as personal, informative and political in nature.\\n\\n\\nOriginality/value\\nThe present study provides insights likely to be of interest to researchers, health organizations, citizens, government and politicians that are interested in making more effective use of social media for the purposes of health promotion. The authors also provide novel insights into the key topics of discussions, websites and hashtags used by Pakistani Twitter users during the COVID-19 pandemic.\\n\",\"PeriodicalId\":43488,\"journal\":{\"name\":\"Information Discovery and Delivery\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2021-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Discovery and Delivery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/idd-03-2021-0022\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Discovery and Delivery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/idd-03-2021-0022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Social network analysis of Twitter data from Pakistan during COVID-19
Purpose
The use of social media has increased during the COVID-19 pandemic. Social media platforms provide opportunities to share news, ideas and personal stories. Twitter is used by citizens in Pakistan to respond and comment on emerging news stories and events. However, it is not known whether Twitter played a positive or negative role in spreading updates and preventive messages during the COVID-19 pandemic. The purpose of this study is to analyse content from Twitter during the pandemic.
Design/methodology/approach
NodeXL was used to retrieve data using the keyword وائرس کورونا (written in Urdu and which translates to Coronavirus). The first data set (Case Study 1) was based on 10,284 Twitter users from the end of March. The second data set (Case Study 2) was based on 10,644 Twitter users from the start of April. The theoretical lens of effective message framing was used to classify the most retweeted content on Twitter.
Findings
Twitter was used for personal and professional projections and included certain tweets included political motives even during the unfolding health crisis. There appeared to be very few successful attempts to use Twitter as a tool for health awareness and risk communication. The empirical findings indicate that the most retweeted messages were gain-framed and can be classified as personal, informative and political in nature.
Originality/value
The present study provides insights likely to be of interest to researchers, health organizations, citizens, government and politicians that are interested in making more effective use of social media for the purposes of health promotion. The authors also provide novel insights into the key topics of discussions, websites and hashtags used by Pakistani Twitter users during the COVID-19 pandemic.
期刊介绍:
Information Discovery and Delivery covers information discovery and access for digital information researchers. This includes educators, knowledge professionals in education and cultural organisations, knowledge managers in media, health care and government, as well as librarians. The journal publishes research and practice which explores the digital information supply chain ie transport, flows, tracking, exchange and sharing, including within and between libraries. It is also interested in digital information capture, packaging and storage by ‘collectors’ of all kinds. Information is widely defined, including but not limited to: Records, Documents, Learning objects, Visual and sound files, Data and metadata and , User-generated content.