[Dataset] Does Volunteer Engagement Pay Off? An Analysis of User Participation in Online Citizen Science Projects

Explanation/Overview:

Corresponding dataset for the analyses and results achieved in the CS Track project in the research line on participation analyses, which is also reported in the publication "Does Volunteer Engagement Pay Off? An Analysis of User Participation in Online Citizen Science Projects", a conference paper for the conference CollabTech 2022: Collaboration Technologies and Social Computing and published as part of the Lecture Notes in Computer Science book series (LNCS,volume 13632) here. The usernames have been anonymised.

Purpose:

The purpose of this dataset is to provide the basis to reproduce the results reported in the associated deliverable, and in the above-mentioned publication. As such, it does not represent raw data, but rather files that already include certain analysis steps (like calculated degrees or other SNA-related measures), ready for analysis, visualisation and interpretation with R.

Relatedness:

The data of the different projects was derived from the forums of 7 Zooniverse projects based on similar discussion board features. The projects are: 'Galaxy Zoo', 'Gravity Spy', 'Seabirdwatch', 'Snapshot Wisconsin', 'Wildwatch Kenya', 'Galaxy Nurseries', 'Penguin Watch'.

Content:

In this Zenodo entry, several files can be found. The structure is as follows (files and folders and descriptions).

corresponding_calculations.html

Quarto-notebook to view in browser

corresponding_calculations.qmd

Quarto-notebook to view in RStudio

assets

data

annotations

annotations.csv

List of annotations made per day for each of the analysed projects

comments

comments.csv 

Total list of comments with several data fields (i.e., comment id, text, reply_user_id)

rolechanges

478_rolechanges.csv

List of roles per user to determine number of role changes 

1104_rolechanges.csv

...

...

totalnetworkdata

Edges 

478_edges.csv

Network data (edge set) for the given projects (without time slices)

1104_edges.csv

...

...

Nodes 

478_nodes.csv 

Network data (node set) for the given projects (without time slices)

1104_nodes.csv 

...

...

trajectories

Network data (edge and node sets) for the given projects and all time slices (Q1 2016 - Q4 2021)

478 

Edges 

edges_4782016_q1.csv

edges_4782016_q2.csv

edges_4782016_q3.csv

edges_4782016_q4.csv

...

Nodes 

nodes_4782016_q1.csv

nodes_4782016_q4.csv

nodes_4782016_q3.csv

nodes_4782016_q2.csv

...

1104 

Edges 

...

Nodes 

...

...

scripts

datavizfuncs.R

script for the data visualisation functions, automatically executed from within corresponding_calculations.qmd

import.R

script for the import of data, automatically executed from within corresponding_calculations.qmd

corresponding_calculations_files

files for the html/qmd view in the browser/RStudio

Grouping:

The data is grouped according to given criteria (e.g., project_title or  time). Accordingly, the respective files can be found in the data structure