Circadian Rhythms and Social Media Information-Sharing

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Abstract

Large amounts of information are shared through social media. Such communication assumes users are sufficiently aligned, not only in terms of their interests but also in terms of their emotional and cognitive states. It is not clear how this emotional and cognitive alignment is achieved for social media, given one-to-one interactions are infrequent and discussion often spans loosely connected individuals. This study argues that circadian rhythms play an important physiological role in aligning users for information-sharing, as information shared at different times of the day is likely to encounter users with common physiological states. Data are gathered from Twitter to examine patterns of sentiment and text complexity in social media, as well as how these patterns affect information-sharing. Results suggest the timing of a social media post, relative to collective patterns of sentiment and text complexity, is a better predictor of information-sharing than the sentiment and text complexity of the post itself. Put differently, information is more likely to be shared when it is posted at times of the day when other users are primed for emotion and concentration, independent of whether that posted information is itself emotional or demanding in concentration.
Original languageEnglish
Title of host publicationInformation Systems and Neuroscience : NeuroIS Retreat 2019
EditorsFred D. Davis, René Riedl, Jan vom Brocke, Pierre-Majorique Léger, Adriane Randolph, Thomas Fischer
Number of pages11
Place of PublicationCham
PublisherSpringer
Publication date2020
Pages1-11
ISBN (Print)9783030281434
ISBN (Electronic)9783030281441
DOIs
Publication statusPublished - 2020
EventNeuroIS Retreat 2019 - Vienna, Austria
Duration: 4 Jun 20196 Jun 2019
http://www.neurois.org/neurois-retreat-2019/

Conference

ConferenceNeuroIS Retreat 2019
Country/TerritoryAustria
CityVienna
Period04/06/201906/06/2019
Internet address
SeriesLecture Notes in Information Systems and Organisation
Volume32
ISSN2195-4968

Keywords

  • Circadian
  • Social media
  • Sentiment
  • Text complexity
  • Twitter

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