Networks

Can you introduce me to Phoebe?

Networks
Nodes
Edges
Centrality
Published

May 27, 2024

Modified

July 30, 2024

Abstract
How entities and individuals are connected and the interactions that take place over this fabric of connections. Who emerges as the go-to person and who is the go-through person!

What graphs will we see today?

Variable #1 Variable #2 Chart Names Chart Shape
Qual Quant (optional) Network Chart

What kind of Data Variables will we choose?

No Pronoun Answer Variable/Scale Example What Operations?
3 How, What Kind, What Sort A Manner / Method, Type or Attribute from a list, with list items in some " order" ( e.g. good, better, improved, best..) Qualitative/Ordinal Socioeconomic status (Low income, Middle income, High income),Education level (HighSchool, BS, MS, PhD),Satisfaction rating(Very much Dislike, Dislike, Neutral, Like, Very Much Like) Median,Percentile

Inspiration

How do these Chart(s) Work?

Plotting a Network Chart

Dataset: The Game of Thrones

Here is a dataset from Jeremy Singer-Vine’s blog, Data Is Plural. This is a list of all books banned in schools across the US.

Download this data to your machine and use it in Orange.

Examine the Data

Figure 1: Banned Books Data Table
Figure 2: Banned Books Data Summary

states that we have 1586 rows, 7 columns. So 1586 banned books are on this list! 🙀 🙀 🙀

The already has a thumbnail-like bar chart. We will still make a “proper” one with the appropriate widget.

Data Dictionary

NoteQuantitative Data
NoteQualitative Data

Research Questions

Note

Q1.

Note

Q2.

What is the Story Here?

  • And what, Californians are too busy making money to care about book-banning!!! The state does not even show up in the chart! 😂

Your Turn

  1. AiRbnb Price Data on the French Riviera:
  1. Apartment price vs ground living area:
  1. Fertility: This rather large and interesting Fertility related dataset from https://vincentarelbundock.github.io/Rdatasets/csv/AER/Fertility.csv

Wait, But Why?

  • Networks show up in a very diverse set of domains: society, epidemiology, trade, logistics, transportation, innovation, ecology, geopolitics, information technology, cyber***…So it’s worthwhile to have a good grounding in networks.
  • In SMI, we wave hands and fatuously say “Everything’s connected”! Well, this module will enable you to go beyond tawk and do a show instead. 
  • Complex relationships between entities are best represented with a graph. 
  • There are also many graph layouts possible for the same dataset. Go see the pictures at David Schoch’s website. This can enable a very different view and insight about these relationships.

References

  1. Network Repository. An Interactive Scientific Network Data Repository: the first scientific network data repository with interactive visual analytics. https://networkrepository.com > A great source of network data from various domains!

  2. https://bookdown.org/markhoff/social_network_analysis/

  3. EpiModel: Mathematical Modeling of Infectious Disease Dynamics. https://www.epimodel.org

  4. Hua Wang, & Wellman, B. (2010). Social Connectivity in America: Changes in Adult Friendship Network Size From 2002 to 2007. American Behavioral Scientist, 53(8), 1148–1169.

  5. Konrad M. Lawson, Toilers and Gangsters:Simple Network Visualization with R for Historians

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