News Organizations’ Selective Link Sharing as Gatekeeping: A Structural Topic Model Approach
To disseminate their stories efficiently via social media, news organizations make decisionsthat resemble traditional editorial decisions. However, the decisions for social media maydeviate from traditional ones because they are often made outside the newsroom and guidedby audience metrics. This study focuses on selective link sharing as quasi-gatekeeping onTwitter – conditioning a link sharing decision about news content. It illustrates how selectivelink sharing resembles and deviates from gatekeeping for the publication of news stories.Using a computational data collection method and a machine learning technique calledStructural Topic Model (STM), this study shows that selective link sharing generates adifferent topic distribution between news websites and Twitter and thus significantly revokesthe specialty of news organizations. This finding implies that emergent logic, which governsnews organizations’ decisions for social media can undermine the provision of diverse news,which relies on journalistic values and norms.