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INFS5730 – Social Media and Enterprise 2.0
Individual Assignment – Social Network Analysis
In this individual assignment you are required to conduct a Social Network Analysis using the software NodeXL and submit a report on Moodle course site through Turnitin. The due date of this assignment is on Week 5, 5:00pm Friday 18th March 2022 (AEDT).
Please note that this assignment is worth 15% of your overall course mark.

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Requirements
Space Exploration Technologies Corp called SpaceX is an American aerospace manufacturer, a provider of space transportation and internet communications services located in Hawthorne, California. SpaceX company was founded by Elon Musk in 2002. Among many other social media influencers, Elon Musk is actively engaged in online conversations with his followers/fans on Twitter to share news about SpaceX, provide updates about Starlink communications satellites and SpaceX rocket launches, etc.
In this assignment, you are working as a Social Media Analyst at SpaceX, and you are asked by your manager to conduct a Social Network Analysis to identify the key influencers who are actively engaged in Twitter conversations about SpaceX. Your manager asked you to focus on the analysis of conversations including the hashtag #spacex posted by SpaceX in its official tweets, and also the hashtag #spacex posted by SpaceX fans in their tweets and replies, as illustrated below.
CRICOS Provider Code 00098G

In your analysis, you have decided to focus on tweets mentioning the hashtag #spacex as well as replies to these tweets. To help you collect the data needed for Social Network Analysis, you will use the “Network Tool” available at https://osome.iu.edu/tools/networks/ as follows:
• Visit the link above to load the tool in your browser.
• In the Hashtag field, type #spacex
• Set the Start date to 30 days in the past to collect data about the last 30 days
• Leave the End date to its default value (current date)
• Select the Network type “Mentions and Replies”
• Click on the “Generate Graph” button.

After the data is automatically extracted from Twitter and the graph generated, you can visualise the graph in 3D as illustrated below. Click on the button “Export” and select “Download CSV” to save the dataset to your computer. You will use that file to analyse the data in NodeXL.
Part 1. Upload the CSV file to Moodle using the link provided under section “Individual Assignment”. (Worth 10% of the available marks).
Part 2. Using NodeXL, conduct a Social Network Analysis of the data obtained in the previous step. The objective of this task is to assess the reply-to-tweet relationship between users.
Submit a Word document reporting the results of the social network analysis of the dataset using NodeXL including the following:
1. Explain who are the actors/users included in the dataset (nodes), we do not look for names? How do they engage in the network (edges)? (Worth 10% of the available marks). (1 page max)
2. Should the network be treated as directed or undirected? Explain the difference between directed and undirected network? Justify your answer with examples (Worth 15% of the available marks). (1 page max)
3. Provide a screenshot of the NodeXL graph pane (in Document Actions) with labelled nodes using an appropriate algorithm to lay out the graph. Explain the reasons behind the choice of the algorithm. (Worth 15% of the available marks). (2 pages max)
4. Provide the following graph metrics from the social network analysis that you generate using NodeXL (Overall Metrics sheet) including a screenshot of the Overall Metrics sheet. Provide an explanation of each metric and a discussion of the findings (worth 30% of the available marks). (2 pages max)
a. Vertices

b. Unique Edges
c. Edges With Duplicates
d. Graph Density
5. Based on your Social Network Analysis, explain how would you identify the “best influencer” among users in the dataset? Justify your answer with examples from your findings. (Worth 20% of the available marks). (1 page max)
Submission instructions
Please submit a word document to the Turnitin assessment submission link on Moodle.
Late submission will incur a penalty of 5% per day or part thereof (including weekends) from the due date and time. An assessment will not be accepted after 5 days (120 hours) of the original deadline unless special consideration has been approved. An assignment is considered late if the requested format, such as hard copy or electronic copy, has not been submitted on time or where the ‘wrong’ assignment has been submitted.
There is no word limit perse, just a page limit as described in the requirements above. Font should be no smaller than Arial 12, with standard margins. The spacing must be 1.5. Please note that material exceeding the page limit will not be considered when grading the assignment.

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