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COMP7025 – Social Network Media Intelligence – Western Sydney University

Assignment Task

Aim

The Project requires us to analyse social media data using the knowledge obtained from this unit with assistance from a computer based statistical package. For this project, we will focus on analysing data from Mastodon.

Method

To complete this project:

  1. Read through this specification
  2. Complete the data analysis required by the specification
  3. Write up your analysis using your favourite word processing/typesetting program, making sure that all of the working is shown and that is it presented well.
  4. Include the student declaration text on the front page of your Please make sure that your name and student number are clearly displayed on the front page.

Project Description

The Department of Education has hired your consulting company to investigate the effect of social networks on student learning. They believe that students with strong friendship groups are more likely to obtain higher grades and so they want you to investigate the structure of a student social network. Perform this analysis using R with the rtoot and igraph libraries. Use the rtoot documentation to find functions that will assist your analysis:

1. Gathering the Network

Use the rtoot library in R to connect to the Mastodon API and download the set of toots that contain the hashtag #WSUCOMP7025. Write the code to use the downloaded data to provide a table showing each server (e.g. mastodon.social) and the count of the number of toots containing #WSUCOMP7025 provided by that server.

2. Following Graph

For each toot author obtained, download the details of the accounts that they follow and write the code to create a directed graph showing each author as a node and the edges showing who follows who. Compute the number of components in the graph and the size of each component. Plot the largest component of the graph (do your best to make it visually appealing). Comment on the structure of the graph. For the remainder of the project, we will only use the largest component of the graph.

3. Graph Statistics

Compute and report the diameter and density of the graph. Plot the in-degree distribution of the graph and estimate the Power Law coefficient ( c ) from the in-degree distribution. Briefly explain what this coefficient reveals about the graph.

4. Graph Structure

The Web can be shown to have a “Giant Strongly Connected” Component, an “In” component, and “Out” component, and also have tendrils and tubes. Decompose the author graph into these components and provide a plot clearly showing each component.

5. Account Popularity

The popularity of each Mastodon account can be measured using PageRank. Measure the popularity of each Mastodon account using the Scaled PageRank algorithm, with α = 0 . 85. Report the ten most popular accounts and their PageRank score, and compare the results to the in-degree of each vertex.

Write up a report containing your code and analysis of the data with each section clearly labelled. Clearly annotate your code and make sure to state any conclusions you make from each piece of analysis. The report is being marked using the marking criteria, so make sure that each piece of analysis covers all of the criteria.

Remember that you are examining the structure of a student social network for the Department of Education, so make sure that the conclusion of each section refers back to this.

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