Constructing and Analysing a Twitter Network - IT Assignment Help

Assignment Task:

Task:

Purpose
The purpose of this CA is to help you learn how to systematically analyse social media data. You will use NodeXL to extract network data from Twitter and identify important aspects of the network.

Practical Nos. 5 and 6 will help you prepare for this assignment.
The quality of the analysis and visualisations you can produce depends on the quality of the dataset you construct, and you may find that you need to vary the search terms and topics in order to create a suitable dataset. Because of this, you must confirm (with your professor) that your dataset is adequate, before starting the analysis.
I am available to give you advice and feedback on (i) the dataset construction, and (ii) a draft of the report.

Step 1. Use NodeXL to import the data you want to analyse
On the left-hand side of the NodeXL Ribbon is an Import dropdown from which you can choose the appropriate import form (i.e., Twitter User, Facebook, Email). Fill in the form to capture the data you want. Use the built-in Help feature if you need more details about the built-in importers. It may take a while for the data to download, especially if it is from Twitter, so plan your time accordingly.

Ideally, you’ll be working with a network of between 300-1000 nodes (users), and 1,500-2,000 edges (tweets). Your biggest danger will be attempting to import networks which are too big (and therefore take a long time to process). If you fail to retrieve enough data, you can try a different search term or hashtag (there is no problem combining the results of multiple searches). Remember that the dataset that you use should be agreed with me BEFORE you start your report.
 

Step 2. Create metrics and calculate clusters
Calculate groups by going to the Groups dropdown and choosing “Group by Cluster Algorithm”.
Calculate graph metrics using the Graph Metrics button on the NodeXL ribbon (make sure you

calculate all of the metrics by checking all of the boxes). Go to the Vertices worksheet and sort based on the different network metrics columns to see who shows up at the “top” (i.e., is the most important). Is it who you expect? Note that some people are important according to one metric (e.g., Betweenness Centrality), while others are important according to another metric (e.g., Degree).
 

Step 3. Visualise Your Network
Click on the Show Graph. Try some different network layouts from the dropdown (e.g., Fruchterman-Reingold, Harel Koren Fast Multiscale, Circle). You may want to look at the Layout Options (available via the Layout drop-down) and try some of the advanced layout features (i.e., layout by group). You may also want to use curved edges, available via the Graph Options window. Once you find a layout you like,

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