#Covid-19: An exploratory investigation of hashtag usage on Twitter

被引:24
|
作者
Petersen, Kai [1 ,2 ]
Gerken, Jan M. [1 ]
机构
[1] Univ Appl Sci Flensburg, Kanzleistr 91-93, D-24943 Flensburg, Germany
[2] Blekinge Inst Technol, Dept Software Engn, Karlskrona, Sweden
关键词
Covid-19; Hashtags; Twitter;
D O I
10.1016/j.healthpol.2021.01.001
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: The literature highlights Twitter as a vital instrument tool for health policy-makers for health communication and promotion. Furthermore, Twitter is a tool allowing us to understand the focus of people regarding a topic of interest. Objective: To provide health policy-makers with insights concerning key topics of interest in the Twitter community regarding Covid-19, and to support information search and health communication. Method: A total of 28.5M tweets have been retrieved, of which 6.9M tweets included hashtags. The data was analyzed using data science and natural language processing libraries. Qualitative analysis was performed using thematic analysis. Results: 907k different hashtags were used. Of these, only 1192 hashtags were used more than 1000 times. The qualitative analysis resulted in 13 themes. The top three themes regarding the number of hashtags used were related to Covid-19, identifying information, interventions, and geographical tagging. We explored the relationship between themes and showed how health practitioners can understand the communication in relation to specific topics expressed as hashtags (e.g., #stayhome). Conclusions: The results provide first insights for policy-makers and health practitioners to identify rel-evant tweets and to choose appropriate hashtags for health communication. The results also show that only with a limited number of Tweets (10 per day) health organizations could have been among the top users. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:541 / 547
页数:7
相关论文
共 50 条
  • [41] Ageism on Twitter during the COVID-19 pandemic
    Ng, Reuben
    Indran, Nicole
    Liu, Luyao
    JOURNAL OF SOCIAL ISSUES, 2022, 78 (04) : 842 - 859
  • [42] A Look into COVID-19 Vaccination Debate on Twitter
    Malagoli, Larissa
    Stancioli, Julia
    Ferreira, Carlos H. G.
    Vasconcelos, Marisa
    Couto da Silva, Ana Paula
    Almeida, Jussara
    PROCEEDINGS OF THE 13TH ACM WEB SCIENCE CONFERENCE, WEBSCI 2021, 2020, : 225 - 233
  • [43] Usage and engagement with Instagram by dermatology residency programs during the COVID-19 pandemic compared with Twitter and Facebook
    Harp, Taylor
    Szeto, Mindy D.
    Presley, Colby L.
    Meckley, Abigail L.
    Geist, Ryan
    Anderson, Jaclyn
    Laughter, Melissa R.
    Rundle, Chandler W.
    Husayn, Sameeha S.
    Dellavalle, Robert P.
    JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY, 2021, 85 (05) : E313 - E315
  • [44] The Influence of Provaping "Gatewatchers" on the Dissemination of COVID-19 Misinformation on Twitter: Analysis of Twitter Discourse Regarding Nicotine and the COVID-19 Pandemic
    Silver, Nathan
    Kierstead, Elexis
    Kostygina, Ganna
    Tran, Hy
    Briggs, Jodie
    Emery, Sherry
    Schillo, Barbara
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2022, 24 (09)
  • [45] Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set
    Klein, Ari Z.
    Magge, Arjun
    O'Connor, Karen
    Amaro, Jesus Ivan Flores
    Weissenbacher, Davy
    Hernandez, Graciela Gonzalez
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2021, 23 (01)
  • [46] Twitter sentiment analysis for COVID-19 associated mucormycosis
    Singh, Maneet
    Dhillon, Hennaav Kaur
    Ichhpujani, Parul
    Iyengar, Sudarshan
    Kaur, Rishemjit
    INDIAN JOURNAL OF OPHTHALMOLOGY, 2022, 70 (05) : 1773 - +
  • [47] Twitter discussions on breastfeeding during the COVID-19 pandemic
    Jawahar Jagarapu
    Marlon I. Diaz
    Christoph U. Lehmann
    Richard J. Medford
    International Breastfeeding Journal, 18
  • [48] Twitter based sentimental analysis of Covid-19 observations
    Vijayaraj, A.
    Bhavana, K.
    SreeDurga, S.
    Naik, S. Lokesh
    MATERIALS TODAY-PROCEEDINGS, 2022, 64 : 713 - 719
  • [49] Machine Learning Approach for COVID-19 Detection on Twitter
    Amin, Samina
    Uddin, M. Irfan
    Al-Baity, Heyam H.
    Zeb, M. Ali
    Khan, M. Abrar
    CMC-COMPUTERS MATERIALS & CONTINUA, 2021, 68 (02): : 2231 - 2247
  • [50] #BoomerRemover: COVID-19, ageism, and the intergenerational twitter response
    Skipper, Antonius D.
    Rose, Daniel J.
    JOURNAL OF AGING STUDIES, 2021, 57