Making Buying Decisions via Social Network Analysis
I have an interest in the recent financial crisis (a.k.a. mortgage meltdown) so I am constantly looking for good reading material about the topic. This morning I was wondering... "What should I read next?" "Which one book will cover most of the angles of this topic?"
Rather than spend time reading reviews of the popular books on the topic, I followed my own suggestion. Using social network analysis [SNA], I created a book network around the topic of "financial crisis". The data was gathered from Amazon and the map of the most frequently mentioned "also bought" books is displayed above. The map does not rank books by sales volume, though it does show the most popular book on the topic of financial crisis.
The network map above shows how books were bought together and by the same customers: A-->B means that people who bought book A also bought book B. This book network helps us see which books are most influential and most integrated in this topic area. I am looking for ONE book to read on the subject, so I will be examining the "integration" scores of each book in the network.
After gathering the data and putting into my software, the network self organizes into two clusters. The cluster on the left contains mostly economic perspectives on the financial crisis and the books in the small cluster on the right contain more of a political perspective on the crisis. I am more interested in the economic dynamics of the financial crisis so I will focus on the cluster on the left.
Two books emerge at the top of the list of network integration scores [the nodes in the network map are sized according to relative integration scores] -- Too Big to Fail and All the Devils Are Here. They both have many similar connections to other books, so they play similar position in the network -- I could choose either one, and be happy.
Update: Thanks to Laura C. Tisdel, Editor of Too Big to Fail for sending a copy of the book after reading the above!