Session 8 Homework

Hi all,

Pls find uploaded in LMS in 'session 8 folder' two R code files and one data file.

The code and Homework is self-explanatory, for the most part.

Pls follow instructions and use the blog comments or email aashish_pandey@isb.edu in case of any queries.

You HW has two parts. Both individual.

Part 1: Mapping Brand communities based on Affiliations

Run the code in 'session 8 HW code 1.txt'.

Generate the brand association graph with weighted edges.

Run the community detection algorithm on it.

Answer the following Qs in a few slides.

• Which brands seem most 'central' to the network?
• Which 'space' is this? What might brand locations in this space signifiy?
• How many brand communities arise?
• Pick any one brand cluster/ community. Interpret what might be the most important affiliations or attributes driving clustering in it.
• How many singletons (or single member clusters) are there? Speculate on why these brands seem isolated.
• If you're the AXN channel, which brand community do you think is best aligned or affiliated with you? Why?

Part 2: Mapping your Facebook friends communities

Run the code in 'session 8 HW code 2.txt'.

Get access token for FB API as was demo-ed in class.

Pull and save the data - a named friends' list, an anonymized friends list and a listof pages liked.

In a few slides, answer the following Qs:

• Do you see natural groupings arise? Which ones are they? ID them like I had done for my FB example in class and paste that on a Slide.
• List some common network properties associated with your FB graph (transitivity, Avg path length)
• How many communities arise? Average size?
• How many singletons (or single member communities) are there?
• Pick a community to analyze. Use anaonymized graph for this. What are the network peoperties for this community?
• Put your marketing hat on. Write two Qs that you as a Marketer might be interested in after studying the graph.

Deliverable: Three pieces to submit - (i) A PPT that answers Qs posed above. Break PPT into two sections for each part.

Title slide should contain your name PGID.

(ii) the anonymized FB friends' list and (iii) the liked pages list.

Pls zip these into a folder titled yourName.zip and submit into appropriate dropbox.

Deadline: Midnight Tuesday 30-sept.

Tight deadline, I know. But the code runs smoothly, will be done in minutes.

My suggestion - do the HWs in a group. If any one person in your group has solved their HW by running the R code, pls borrow and share the results with peers.

After all, its the interpretation of the analysis and not running the analysis that this HW hinges on.

Part 1 is common to everyone anyway.

Any queries, contact aashish or me.

Sudhir