COMMUNICATION NETWORK ANALYSIS OF THE ANTI-RACISM TOWARDS ASIAN CAMPAIGN ON TWITTER
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Abstract
This study aims to determine the distribution of communication networks of the
#StopAsianHate campaign on Twitter. Using the theory of Computer-Mediated
Communication, this paper seeks to identify the campaign's networks in system level and actor
level. To achieve this, we used a quantitative approach of Communication Network Analysis
with the Netlytic and Gephi models, as well as the content analysis method. From the analysis,
we found 5 independent clusters in the network. On the level system, we found that information
exchange requires only 2 actors to be passed, actors retweet or like more than talk, most
conversations happened one-sidedly, network dominated by few actors, and network has a
clear division between the clusters represented. On the actor level, we identified two accounts
that played a dominating role in the campaign, that actors have a close relationship with other
actors, no influence in linking the distribution of information related, and found 6 top actors
with central role. Meanwhile, from the content analysis we found that the focus of the actor's
communication campaign is the sharing of opinions, information, and images.
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