Cern#

Social media engagements of 4 different types of posts on 4 different platforms by The European Organization for Nuclear Research, better known as CERN.

From the authors: “Although the scientific community increasingly recognizes that its communication with the public may shape civic engagement with science, few studies have characterized how this communication occurs online. This study sets out to explore how users engage with science communication items on different platforms of social media, and what are the characteristics of the items that tend to attract large numbers of user interactions.”

Initialization#

library(fosdata)
data <- fosdata::cern

Accessing fields#

data <- fosdata::cern
subject <- data$subject # Just a random field in the dataset

Interactive R Sample#

You can use the R editor below to interactively explore the dataset and generate plots. This contains a fully self-contained R environment with fosdata, ggplot2, and dplyr loaded.

No plot generated yet.

LLM instructions#

If using an LLM, you can copy-paste the following instructions to accompany your prompt to inform the model of the fields and their types in the dataset.

The fosdata::cern dataset containing the following fields:

fields[11]{name,type,values}:
  postdate,character,n/a
  platform,factor,[Facebook,Google+,Twitter,Instagra,Tw Frenc]
  type,factor,[GWII,News,Wow,TBT]
  subject,character,n/a
  followers,integer,n/a
  likes,numeric,n/a
  comments,numeric,n/a
  shares,numeric,n/a
  click_throughs,numeric,n/a
  avg_visit_duration,numeric,n/a
  post,character,n/a

Fields#

Source#

Kahle K, Sharon AJ, Baram-Tsabari A (2016) Footprints of Fascination: Digital Traces of Public Engagement with Particle Physics on CERN’s Social Media Platforms. PLoS ONE 11(5): e0156409. https://doi.org/10.1371/journal.pone.0156409