Publication | Closed Access
Spreading the Good News: Analyzing Socially Shared Inspirational News Content
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Citations
32
References
2018
Year
CommunicationMedia StudiesJournalismInteractive JournalismMedia ActivismSocial MediaNews AnalyticsSocial Medium NewsNews SemanticsContent AnalysisMedia PsychologySelf-transcendent Language UseMedia ContentPopular CommunicationPast ResearchCreative NonfictionSocial ComputingNew York TimesMass CommunicationArtsSocial Medium DataGood News
Past research indicates that people often share awe-inspiring news online. However, little is known about the content of those stories. In this study, more broadly defined “inspirational” articles shared through The New York Times website over a 6-month period were analyzed, with the goals of describing the content and identifying characteristics that might predict inspirationality and measures of retransmission. The results provided a snapshot of content found within inspirational news stories; they also revealed that self-transcendent language use predicted the inspirationality of a news story, as well as how long an article appeared on a most shared list.
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