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To understand the opinions of the people, many government departments check online news outlets to manually detect events that interest people. This process is time-consuming. To promptly respond to public expectations, this research proposes a framework for detecting news events that may interest government departments. This article proposes a method for finding event trigger words used to represent an event. The news media can be a critical participant in \u2018agenda-setting\u2019, which means that more widely discussed news is more attractive and critical than news that is less discussed. However, few studies have considered the influence of news media publishers from the \u2018agenda setting\u2019 perspective. Therefore, this study proposes an \u2018agenda setting\u2019-based filter to establish a high-impact news event detection model. The proposed framework identifies trigger words and utilises word embedding to find news event\u2013related words. After that, an event detection model is designed to determine the events that are attractive to government departments. The experimental results show that purity increases from 0.666 when no extraction method is used to 0.809 when the extraction method in this study is used. 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