Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
This study investigated the role of circadian rhythms in online information sharing. We gathered 416,914 posts from the social media platform X (formerly Twitter). We identified daily patterns of collective positive and negative affect in these posts, consistent with previous research on social media and circadian rhythms. We created predicted values of positive and negative affect for each post, based on the time a post was created. We then used these predicted values for each post to estimate that post's likelihood of being reshared. We controlled for a range of possible confounders, such as the actual positive and negative affect expressed in a specific post and the number of existing followers and previous posts of the user who created the post, as well as whether the post contained hashtags, mentions, and quotes. The results support a strong relationship between the predicted positive and negative affect of a post-based on circadian patterns of collective positive and negative affect-and the likelihood of a post being shared. We further examine seasonal changes and design a natural experiment, in which we compare patterns of positive and negative affect and information sharing before and after the clocks change, i.e., "spring forward" and "fall back." The results suggest that these daily collective patterns of positive and negative affect on social media are influenced, at least partly, by hormonal influences and not only collective daily routines.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11624179 | PMC |
http://dx.doi.org/10.1007/s42761-024-00254-0 | DOI Listing |
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