Cargando…
A neural model of valuation and information virality
Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that e...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358393/ https://www.ncbi.nlm.nih.gov/pubmed/28242678 http://dx.doi.org/10.1073/pnas.1615259114 |
_version_ | 1782516222453088256 |
---|---|
author | Scholz, Christin Baek, Elisa C. O’Donnell, Matthew Brook Kim, Hyun Suk Cappella, Joseph N. Falk, Emily B. |
author_facet | Scholz, Christin Baek, Elisa C. O’Donnell, Matthew Brook Kim, Hyun Suk Cappella, Joseph N. Falk, Emily B. |
author_sort | Scholz, Christin |
collection | PubMed |
description | Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies (n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain's value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing—to express ourselves in positive ways and to strengthen our social bonds. |
format | Online Article Text |
id | pubmed-5358393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-53583932017-03-24 A neural model of valuation and information virality Scholz, Christin Baek, Elisa C. O’Donnell, Matthew Brook Kim, Hyun Suk Cappella, Joseph N. Falk, Emily B. Proc Natl Acad Sci U S A Social Sciences Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies (n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain's value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing—to express ourselves in positive ways and to strengthen our social bonds. National Academy of Sciences 2017-03-14 2017-02-27 /pmc/articles/PMC5358393/ /pubmed/28242678 http://dx.doi.org/10.1073/pnas.1615259114 Text en Freely available online through the PNAS open access option. |
spellingShingle | Social Sciences Scholz, Christin Baek, Elisa C. O’Donnell, Matthew Brook Kim, Hyun Suk Cappella, Joseph N. Falk, Emily B. A neural model of valuation and information virality |
title | A neural model of valuation and information virality |
title_full | A neural model of valuation and information virality |
title_fullStr | A neural model of valuation and information virality |
title_full_unstemmed | A neural model of valuation and information virality |
title_short | A neural model of valuation and information virality |
title_sort | neural model of valuation and information virality |
topic | Social Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358393/ https://www.ncbi.nlm.nih.gov/pubmed/28242678 http://dx.doi.org/10.1073/pnas.1615259114 |
work_keys_str_mv | AT scholzchristin aneuralmodelofvaluationandinformationvirality AT baekelisac aneuralmodelofvaluationandinformationvirality AT odonnellmatthewbrook aneuralmodelofvaluationandinformationvirality AT kimhyunsuk aneuralmodelofvaluationandinformationvirality AT cappellajosephn aneuralmodelofvaluationandinformationvirality AT falkemilyb aneuralmodelofvaluationandinformationvirality AT scholzchristin neuralmodelofvaluationandinformationvirality AT baekelisac neuralmodelofvaluationandinformationvirality AT odonnellmatthewbrook neuralmodelofvaluationandinformationvirality AT kimhyunsuk neuralmodelofvaluationandinformationvirality AT cappellajosephn neuralmodelofvaluationandinformationvirality AT falkemilyb neuralmodelofvaluationandinformationvirality |