Spreading the Good News: Analyzing Socially Shared Inspirational News Content

Qihao Ji; Arthur A. Raney; Sophie H. Janicke-Bowles; Katherine R. Dale; Mary Beth Oliver; Abigail Reed; Jonmichael Seibert; Arthur A. Raney

doi:10.1177/1077699018813096

Spreading the Good News: Analyzing Socially Shared Inspirational News Content

Qihao Ji
, Arthur A. Raney
, Sophie H. Janicke-Bowles
, Katherine R. Dale
, Mary Beth Oliver
, Abigail Reed
, Jonmichael Seibert
, Arthur A. Raney

Film-Video and Media Studies

Research output: Contribution to journal › Article › peer-review

41 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	872-893
Number of pages	22
Journal	Journalism and Mass Communication Quarterly
Volume	96
Issue number	3
DOIs	https://doi.org/10.1177/1077699018813096
State	Published - Sep 1 2019

All Science Journal Classification (ASJC) codes

Communication

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10.1177/1077699018813096

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title = "Spreading the Good News: Analyzing Socially Shared Inspirational News Content",

abstract = "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.",

author = "Qihao Ji and Raney, \{Arthur A.\} and Janicke-Bowles, \{Sophie H.\} and Dale, \{Katherine R.\} and Oliver, \{Mary Beth\} and Abigail Reed and Jonmichael Seibert and Raney, \{Arthur A.\}",

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TY - JOUR

T1 - Spreading the Good News

T2 - Analyzing Socially Shared Inspirational News Content

AU - Ji, Qihao

AU - Raney, Arthur A.

AU - Janicke-Bowles, Sophie H.

AU - Dale, Katherine R.

AU - Oliver, Mary Beth

AU - Reed, Abigail

AU - Seibert, Jonmichael

AU - Raney, Arthur A.

PY - 2019/9/1

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AB - 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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Spreading the Good News: Analyzing Socially Shared Inspirational News Content

Abstract

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