Network Model for Online News Media Landscape in Twitter

Abstract

Today, most studies of audience networks analyze the landscape of the news media on the web. However, media ecology has been drastically reconfigured by the emergence of social media. In this study, we use Twitter follower data to build an online news media network that represents the pattern of news consumption in Twitter. This study adopted a weighted network model proposed by Mukerjee et al. and implemented the Filter Disparity Method suggested by Majó-Vázquez et al. to identify the most significant overlaps in the network. The implementation result on news media outlets data in three countries, namely Indonesia, Malaysia, and Singapore, shows that network analysis of follower overlap data can offer relevant insights about media diet and the way readers navigate various news sources available on social media.

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