The Value of Netnography for Research in HRD

This paper argues for recognition of Netnography as a necessary methodological innovation for HRD research, enabling the field to address emerging research questions and contribute to theory building at the intersection of technology, work and social life. The paper defines ‘netnography’ and introduces its key methodological underpinnings; illustrates its application and procedures; and considers its benefit to HRD research. We identify three opportunities where Netnography can deliver important advances to HRD theory and practice: investigating hard-to-access online work contexts, such as gig work and other forms of precarious working; exploring marginalised, ‘hidden’, or under-researched voices in online spaces; and extending knowledge of learning in hybrid work environments where physical and digital dimensions are intertwined. We conclude with a call to action by HRD scholars to take forward, and further develop, the Netnographic methodology to contribute to new and inclusive theorizing as a basis for advancements in HRD scholarship and practice.

The dramatic increase in anti-vaccine discourses during the COVID-19 pandemic: a social network analysis of Twitter

Background/Aim

The first case of COVID-19 in Turkey was officially recorded on March 11, 2020. Social media use increased worldwide, as well as in Turkey, during the pandemic, and conspiracy theories/fake news about medical complications of vaccines spread throughout the world. The aim of this study was to identify community interactions related to vaccines and to identify key influences/influencers before and after the pandemic using social network data from Twitter.

Materials and methods

Two datasets, including tweets about vaccinations before and after COVID-19 in Turkey, were collected. Social networks were created based on interactions (mentions) between Twitter users. Users and their influence were scored based on social network analysis and parameters that included in-degree and betweenness centrality.

Results

In the pre-COVID-19 network, media figures and authors who had anti-vaccine views were the most influential users. In the post-COVID-19 network, the Turkish minister of health, the was the most influential figure. The vaccine network was observed to be growing rapidly after COVID-19, and the physicians and authors who had opinions about mandatory vaccinations received a great deal of reaction. One-way communication between influencers and other users in the network was determined.

Conclusions

This study shows the effectiveness and usefulness of large social media data for understanding public opinion on public health and vaccination in Turkey. The current study was completed before the implementation of the COVID-19 vaccine in Turkey. We anticipated that social network analysis would help reduce the “infodemic” before administering the vaccine and would also help public health workers act more proactively in this regard.