Anders K. Munk & Mathieu Jacomy

2.5. Do your own network from a category

Duration: 45 min + 45 min

Goals

  • Activate your knowledge
  • Make your own network map from scratch:
    • from sourcing
    • to harvesting,
    • visualization,
    • annotation,
    • and writing the protocol.
  • Contribute to your own group project, at least as a test.

Task

It is now time to go through the whole process you have just learned, but on your own data set and for your own project.

  1. Choose a Wikipedia category
  2. Source a list of its Wikipedia articles
  3. Harvest at least 2 networks
  4. Analyze and visualize them
  5. Annotate your network maps
  6. Write the visual protocols

Advice and comments

  • Help each other!
  • Check the list of notebooks.
  • Pay attention to the quality of the sourcing (the list of articles). The better, the easier the work of analyzing it: check that the articles are actually related to your topic.
  • What size for the sourcing (articles list)?
    • Not too small, not too big: between 100 and 5000, but it also depends.
    • If the subsequent harvesting makes your data bigger (e.g., articles and editors), prefer smaller lists (max level low).
    • If not (e.g., hyperlinks network), you can probably visualize a network of thousands of nodes, and more if you filter it.
    • If you have two, source multiple lists (same category, but at different levels).
  • During network analysis, consider:
    • Filtering your network
    • Computing centrality metrics, then annotating the important nodes
    • Computing modularity clustering, them annotating the clusters
    • Reflecting on the edges’ direction and weight, if any.
  • You may make multiple network maps for the same network.
  • You may make multiple annotated visualizations for a same network map.
  • Prioritize clarity in your visualizations and visual protocols.
  • If it makes more sense, you may join your protocols into a single diagram.
  • Take risks! This is a good occasion to try something uncertain. Data science is a bet, it’s exploration.
  • Take a break at some point. You have a time slot of approximatively 1 hour and 45 minutes, including a 15 minutes break.

Documents produced

Keep somewhere, for sharing, the following documents:

  • The images of the annotated network maps (JPEG or PNG)
  • The image(s) of the visual protocol(s) (JPEG or PNG)

Share your work

Your teachers will provide you with a Padlet where you can share your annotated maps and visual protocols. Make sure that you put them up before you have lunch.

Next tutorial

🥩 Lunch break: take forces!

The afternoon starts with this:

 2.6. Follow the protocol: words, from manual curation to Tableau (45 min)

Tools for getting similar data (networks in GEXF or GDF format) from other sources:

  • Networks of users, hashtags, or emojis from Twitter with the Twitter Streaming Importer plugin for Gephi. Takes a list of words/#tags or a list of users as input.
  • Networks of YouTube channels or YouTube videos connected by their relatedness (as meassured by the algorithmic recommendations) with the YouTube Data Tools. Takes a list of video or channel ID’s as input.
  • Networks of scientific publications connected through keywords or citations with ScienceScape. Takes a full export from Scopus as input.

Relation to the course readings

  • The process of getting data through scraping, crawling and calling APIs is covered in Chapter 6: Collecting and curating digital records of Venturini, T. & Munk, A.K. (2021). Controversy Mapping: A Field Guide.
  • The intricacies of Wikipedia and the different ways in which the platform may be reappropriated for controversy analysis are covered in Weltevrede, E., & Borra, E. (2016). Platform affordances and data practices: The value of dispute on Wikipedia Big Data & Society, 3(1).
  • The principles and concepts of Visual Network Analysis (VNA) are covered in Chapter 2: What is visual network analysis in Jacomy, M. (2021). Situating Visual Network Analysis
  • And in Chapter 7: Visual network analysis in Venturini, T. & Munk, A.K. (2021). Controversy Mapping: A Field Guide
  • An example of how to visualize and annotate the same network of wikipedia articles in different ways is described in Figures 62-65 of Venturini, T. & Munk, A.K. (2021). Controversy Mapping: A Field Guide:

CM Figure 62 Two renderings of a network of Wikipedia pages related to the Green Revolution. Top, density heatmap and structural holes; bottom, clusters and sub-clusters

CM Figure 63 Central (continuous contour) and bridging (dotted line) nodes in the Green Revolution networks

CM Figure 64 Authorities (left) and hubs (right) of the Green Revolution network

CM Figure 65 The Green Revolution network colored according to our manual thematic classification of Wikipedia pages