This project is the Capstone project in the Object Oriented Java Programming: Data Structures and Beyond Specialization. It investigates cascading behaviors (or information flow) within a social network.
When people are connected by a network, it becomes possible for them to influence each other's behavior and decisions. There is a nearly limitless set of situations in which people are influenced by others: in the opinions they hold, the products they buy, the political positions they support, the activities they pursue, the technologies they use, and many other things. What we'd like to do here is to go beyond this observation and consider some of the reasons why such influence occurs.
© Networks, Crowds, and Markets: Reasoning about a Highly Connected World
by David Easley and Jon Kleinberg. Cambridge University Press, 2010.
The first part of this project will look at what the network equilibrium looks like when given certain starting conditions, and after a number of simulations. The second part of the project investigates the maximal conditions under which a complete cascade can occur in a given social network.
- Java SE 8
- Maven
- GraphStream
- JUnit 5
- Any IDE that supports JDK 8
- Download and unzip the project source code.
- From a command line window, navigate to the (newly unzipped) project folder, and then run
mvn clean installcommand. - To launch the application, run
java -jar target/information-flow-1.0.jar. - You're now ready to freely play around with values
Reward AandReward B, and visualize how information cascades through the network.
- Networks, Crowds, and Markets: Reasoning about a Highly Connected World
- Capstone: Analyzing (Social) Network Data
- Object Oriented Java Programming: Data Structures and Beyond Specialization
Copyright (c) 2017 UC San Diego Intermediate Software Development MOOC team
Copyright (c) 2018 Solange Umuhire Gasengayire
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