Emerging issues were not clearly evident and rarely garnered policymakers’ attention until they started to shift into trends and exerted significant influence on society. This study developed a method to identify issues that are likely to become trends in the future, and to prevent researcher bias in issue identification, by using an automated algorithm to filter through a large amount of literature, identified emerging keywords, and formed them into emerging issues.
Using our internally developed emerging issue detection algorithm based on the WoS (Web of Science) database over the past five years and focusing on “conflict” cases, we derived the top 30 keywords that meet the criteria of novelty, scalability, and impact.
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