Twitter Community Discovery & Analysis Using Topologies

1. Twitter Community Discovery & Analysis Using Topologies Andrew McClain Karen Aguar

2. Outline • Introduction • Motivation • Project Description • Our Objective • Community Discovery • Analysis & Application • Data collection • Use of Gephi

3. Introduction • Many people use services like twitter to stay in contact with groups in which they are members or to interact with other people with similar interests • These groups are considered “communities”

4. Community? • A network or group of nodes with greater ties internally than to the rest of the network • There are various derivations of a community: • Some communities are tightly bound together • Others are loose associations of people • Communities can be defined by a quality function • Several quality functions may be used & will vary based on the situations • Experimentally determine the best quality function for our purposes

5. Motivation • We want to classify these communities & find real world implications of their digital associations • Project Description: Discovering communities & examining the properties of the graph to give us insight into the community itself. • Ex: Find the organizers of a hobby group by the twitter activity

6. Our Project Our project can be broken into 2 main sections • Twitter community discovery • Analysis of the community graphs & its correlation to the real world community structure

7. Community Discovery • Select a diverse number of individuals from known real-world communities • Apply local graph clustering to isolate the community that they belong to • Example: CNN • Generate graphs of the communities

8. Analysis & Application • Analyze the relationships in the graphs using a variety of analysis techniques • Detect behavior patterns and structures in twitter communities • Shape, interconnectivity, how the information flows through it • Apply our knowledge to learn about unknown communities based on twitter behavior *time permitting

9. Data Collection • Datasets containing actual tweets are now unavailable due to a change in Twitter’s terms of use. We will collect our own data through the use of: • Twitter Rest API • Gephi -- open source graph visualization platform • Retweet plugin for Gephi

10. Gephi for Community Discovery • We will use Gephi partitioning methods to set different ways of partitioning the graph & use quality functions to determine what is / is not a community. • Gephigives us very powerful filter functions so that we can reduce data down to what we want very quickly

11. References • Community Discovery in Social Networks: Applications, Methods and Emerging Trends • S. Parthasarathy, Y. Ruan, V. Satuluri[2011] • gephi.com • dev.twitter.com