The Library
The more who die, the less we care : evidence from natural language analysis of online news articles and social media posts
Tools
Tools
Tools
Bhatia, Sudeep, Walasek, Lukasz, Slovic, Paul and Kunreuther, Howard (2020) The more who die, the less we care : evidence from natural language analysis of online news articles and social media posts. Risk Analysis, 41 (1). pp. 179-203. doi:10.1111/risa.13582
![[img]](http://wrap.warwick.ac.uk/style/images/fileicons/application_pdf.png) |
PDF
WRAP-The-more-who-die-less-we-care-natural-language-Walasek-2020.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only until 25 August 2022. Contact author directly, specifying your specific needs. - Requires a PDF viewer. Download (1917Kb) |
Official URL: https://doi.org/10.1111/risa.13582
Abstract
Considerable amount of laboratory and survey‐based research finds that people show disproportional compassionate and affective response to the scope of human mortality risk. According to research on “psychic numbing,” it is often the case that the more who die, the less we care. In the present article, we examine the extent of this phenomenon in verbal behavior, using large corpora of natural language to quantify the affective reactions to loss of life. We analyze valence, arousal, and specific emotional content of over 100,000 mentions of death in news articles and social media posts, and find that language shows an increase in valence (i.e., decreased negative affect) and a decrease in arousal when describing mortality of larger numbers of people. These patterns are most clearly reflected in specific emotions of joy and (in a reverse fashion) of fear and anger. Our results showcase a novel methodology for studying affective decision making, and highlight the robustness and real‐world relevance of psychic numbing. They also offer new insights regarding the psychological underpinnings of psychic numbing, as well as possible interventions for reducing psychic numbing and overcoming social and psychological barriers to action in the face of the world's most serious threats.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | B Philosophy. Psychology. Religion > BF Psychology H Social Sciences > HM Sociology Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Psychology | ||||||||
| Library of Congress Subject Headings (LCSH): | Big data , Emotions , Natural language processing (Computer science) , Risk assessment -- Moral and ethical aspects, Sentiment analysis | ||||||||
| Journal or Publication Title: | Risk Analysis | ||||||||
| Publisher: | Wiley-Blackwell Publishing Ltd. | ||||||||
| ISSN: | 0272-4332 | ||||||||
| Official Date: | 2020 | ||||||||
| Dates: |
|
||||||||
| Volume: | 41 | ||||||||
| Number: | 1 | ||||||||
| Page Range: | pp. 179-203 | ||||||||
| DOI: | 10.1111/risa.13582 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Reuse Statement (publisher, data, author rights): | "This is the peer reviewed version of the following article: Bhatia, S., Walasek, L., Slovic, P. and Kunreuther, H. (2020), The More Who Die, the Less We Care: Evidence from Natural Language Analysis of Online News Articles and Social Media Posts. Risk Analysis., which has been published in final form at https://doi.org/10.1111/risa.13582. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions." | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| RIOXX Funder/Project Grant: |
|
||||||||
| Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
