Smart Technologies And Social Media Report
Download the New Zealand’s knowledge network data from the class moodle. It represents
a sample of New Zealand’s publication network that I constructed based on 3,385 computer
science related publications (from 1972-2016); where nodes represent authors and links
represents co-authorship relations. This is a network file (.net) and opened/read by
either NodeXL or Gephi (or any other tool of your choice listed below) to construct and
analyze the network. A tutorial on Gephi is available here: https://gephi.org/users/quick-
start/ and a tutorial on Nodexl is provided in the class resources.
Your goal is to analyse construct the network and then write a short report about this network.
Describe interesting features, important institutions, relationships, etc. This is not something
you can do just by looking at the structure – you will need to analyze network property (both
node level and network level properties). You should provide a deep investigation into this
network. Who are the central institutions/universities? What is their role in the network (e.g.,
their Degree, Betweenness, and Eigenvector Centrality)? What are the big clusters? What does
each represent? How did you find that out? I want a thorough analysis of all the major features
of the network. Figure 1 below is an example of the network that I constructed from the same
data using NodeXL. Where nodes represent institutions and links represent collaboration ties.
In this instance, Node size represents betweenness centrality and link width represents
intensity of collaboration.
Figure 1 New Zealand’s Knowledge Network (Computer Science Field 1972-2016)
Your Final Report & Grading
It is important that in your final report to be analytical rather than descriptive and should
include following analysis:
1. The report includes a meaningful visualization of the network. Try to replicate figure
1 with different colours (I will not accept similar colours). You should filter the network,
for example, highlighting the important nodes, showing intensity of collaboration (e.g., with
links width and colours) (5 marks).
2. The report includes network level statistics (such as, total number nodes, clustering co-
efficient, average degree, density, and diameter) with brief explanation of results. What does
it say about the network? (5 marks).
3. The report includes a list of top 10 nodes (institutions) in terms of degree, betweennes,
and eigenvector centralise accompanied by with brief explanation the results. Instead, give a
meaningful description of who the institutions are, what their role is in the network, and how
their research activities relate to that role, etc. (5 marks).
4. In terms of Eigenvector Centrality, what is the position of Waikato University as
compared to others and what does it mean? (5 marks).
1. Final report should be no more than 1000 words (excluding tables and references),
12-point font, and one-inch margins.
2. Include page numbers to facilitate review.
3. The first page should provide the student name and ID.
4. Use headings and subheadings to facility the review.https://nodexl.codeplex.com/https://gephi.org/users/download/https://gephi.org/users/quick-start/https://gephi.org/users/quick-start/https://elearn.waikato.ac.nz/mod/page/view.php?id=651875https://elearn.waikato.ac.nz/mod/page/view.php?id=651875