Abstract
To end the COVID-19 pandemic, large-scale vaccination schemes have been implemented in more and more countries around the globe since December 2020. However, the steady increase in vaccination rates may be hampered by vaccine hesitancy among individuals who are eligible yet unwilling to receive the shot.
Studies have shown that social media exert a huge impact on people’s attitudes toward vaccination and their intention of uptake. The spread of anti-vaccination messages on popular social networking sites is considered one of the major reasons behind vaccine hesitancy. Thus, it is crucial to understand what types of vaccine-related messages go viral on social media and how differently users interact with pro- and anti-vaccination contents.
The current study adopts a network approach to the diffusion of vaccine-related information on Facebook. In particular, it analyzes coordinated link sharing behavior of Facebook users who coordinately shared the same hyperlinks that are embedded in publicly-available posts related to COVID-19 vaccine and/or vaccination. It intends to compare the diffusion patterns of pro-vaccination messages with those of anti-vaccination ones.
Originally, the concept of coordinated sharing was applied to detecting fake news and political misinformation on Twitter during election times. Similar to co-sharing, it involves two or more users sharing the same content on social media, yet it bears an additional temporal element, such as co-sharing in a time period as short as a few seconds.
As a work-in-progress, this study takes the first step to examine the patterns of coordinated sharing of COVID-19-vaccine-related information among U.S. Facebook users. Of particular interest is the structural characteristics of the coordinated link sharing network and how they relate to source and content characteristics of the original posts. We are especially interested to see whether and how vaccine attitude, operationalized as pro-vaccination, neutral, and anti-vaccination, influences the sharing patterns. We will also explore what information sources are more likely to be shared together.
In this study, we will combine quantitative content analysis with social network analysis to examine the diffusion patterns. We will retrieve data from CrowdTangle and construct a network based on coordinated sharing relationships. More than a conventional hyperlink network, the output will take the form of a projected graph of Facebook entities, including Pages, groups, and public profiles, who shared the URLs in a coordinated way. The edges will be weighted by the number of times a coordinated sharing happened.
The significance of this study is threefold. First, it applies coordinated link sharing to examining normal co-sharing behaviors taking place in a certain time period. By taking time into consideration, it treats the network as dynamic and captures how such a network evolves over time. Second, it explores structural features of the coordinated link sharing network, thus paving way for further analysis of why the network takes the form as it is. Finally, by studying the diffusion patterns of pro- and anti-vaccination messages on social media, we may shed light on the development of effective communication strategies to tackle the prevalence of vaccine hesitancy as vaccines roll out.
Studies have shown that social media exert a huge impact on people’s attitudes toward vaccination and their intention of uptake. The spread of anti-vaccination messages on popular social networking sites is considered one of the major reasons behind vaccine hesitancy. Thus, it is crucial to understand what types of vaccine-related messages go viral on social media and how differently users interact with pro- and anti-vaccination contents.
The current study adopts a network approach to the diffusion of vaccine-related information on Facebook. In particular, it analyzes coordinated link sharing behavior of Facebook users who coordinately shared the same hyperlinks that are embedded in publicly-available posts related to COVID-19 vaccine and/or vaccination. It intends to compare the diffusion patterns of pro-vaccination messages with those of anti-vaccination ones.
Originally, the concept of coordinated sharing was applied to detecting fake news and political misinformation on Twitter during election times. Similar to co-sharing, it involves two or more users sharing the same content on social media, yet it bears an additional temporal element, such as co-sharing in a time period as short as a few seconds.
As a work-in-progress, this study takes the first step to examine the patterns of coordinated sharing of COVID-19-vaccine-related information among U.S. Facebook users. Of particular interest is the structural characteristics of the coordinated link sharing network and how they relate to source and content characteristics of the original posts. We are especially interested to see whether and how vaccine attitude, operationalized as pro-vaccination, neutral, and anti-vaccination, influences the sharing patterns. We will also explore what information sources are more likely to be shared together.
In this study, we will combine quantitative content analysis with social network analysis to examine the diffusion patterns. We will retrieve data from CrowdTangle and construct a network based on coordinated sharing relationships. More than a conventional hyperlink network, the output will take the form of a projected graph of Facebook entities, including Pages, groups, and public profiles, who shared the URLs in a coordinated way. The edges will be weighted by the number of times a coordinated sharing happened.
The significance of this study is threefold. First, it applies coordinated link sharing to examining normal co-sharing behaviors taking place in a certain time period. By taking time into consideration, it treats the network as dynamic and captures how such a network evolves over time. Second, it explores structural features of the coordinated link sharing network, thus paving way for further analysis of why the network takes the form as it is. Finally, by studying the diffusion patterns of pro- and anti-vaccination messages on social media, we may shed light on the development of effective communication strategies to tackle the prevalence of vaccine hesitancy as vaccines roll out.
| Original language | English |
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| Publication status | Published - Jul 2021 |
| Event | Networks 2021: A Joint Sunbelt and NetSci Conference - Virtual Duration: 5 Jul 2021 → 10 Jul 2021 https://networks2021.net |
Conference
| Conference | Networks 2021 |
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| Period | 5/07/21 → 10/07/21 |
| Internet address |
