ArticlePeerJ2019
Likes, comments, and shares of marine organism imagery on Facebook.
Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Motivation to participate in secondary science communication.Frontiers in psychology · 2022Article
- Article
- E Pluribus Octo - Building Consensus on Standards of Care and Experimentation in Cephalopod Research; a Historical Outlook.Frontiers in physiology · 2020Review
- Cerebrotypes in Cephalopods: Brain Diversity and Its Correlation With Species Habits, Life History, and Physiological Adaptations.Frontiers in neuroanatomy · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Several calls to action urge scientists and science communicators to engage more with online communities. While these calls have been answered by a high percentage of scientists and science communicators online, it often remains unclear what are the best models for effective communication. Best practices and methods for online science communication can benefit from experimental and quantitative research addressing how and when users engage with online content. This study addresses with quantitative and predictive models a key question for the popular, but often-ignored in science communication, social media platform Facebook. Specifically, this study examines the impact of imagery through quantification of likes, comments, and shares on Facebook posts. Here, I show that a basic quantitative model can be useful in predicting response to marine organism imagery on Facebook. The results of this online experiment suggest image type, novelty, and aesthetics impact the number of likes, shares, and comments on a post. In addition, the likes, shares, and comments on images did not follow traditional definitions of "charismatic megafauna", with cephalopods and bony fishes receiving more interactions than cartilaginous fishes and marine mammals. Length and quality of caption did not significantly impact likes, comments, or shares. This study provides one of the first quantitative analysis of virality of scientific images via social media. The results challenge previously held conceptions of social media scientific outreach including increasing emphasis on imagery selection and curation, notions of which taxa the public connect with, and role of captions for imagery.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.