Mining%20and%20Visualizing%20the%20Evolution%20of%20Subgroups%20in%20Social%20Networks

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Mining and Visualizing the Evolution of Subgroups
in Social Networks

• Falkowsky, T., Bartelheimer, J. Spiliopoulou,
  M. (2006) IEEE/WIC/ACM International Conference
  on Web Intelligence, pp. 52-58
• Presented by Danielle Lee

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Outline

• Problem
• Research Purpose
• Data Set
• First Approach Statistical Analyses and
  Visualization for relatively stable communities
• Second Approach Detection of the subgroup
  evolution in high fluctuating communities

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Problem

• A community has rather stable structure with a
  small amount of fluctuating members and they
  participate in over a long time.
• Another community has high dynamic structure
  whose members and their networks keep changing
  over time.
• Different community detection and visualization
  methods are needed.

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Research Purpose

• To propose statistical method and visualization
  to analyze the formation of subgroups and the
  timely change of online communities on the level
  of sub-groups

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Data Set

• Taken from an online international student
  community in the University of Magdeburg.
• About 1000 members from more than 50 countries
• 250,000 guestbook entries over a period of 18
  months

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Evolution of Subgroups in Static Structure
(Contd.)

• Mining for subgroups in Social Networks
• Partitioning data by time axis
• Weight graph Gt of interactions between
  individuals for each time windows is built.
• Hierarchical edge betweenness clustering of the
  graph is applied in each time window

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Evolution of Subgroups in Static Structure
(Contd.)
Sub- groups
Communication within one community
Detailed information at a certain time point
time
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Evolution of Subgroups in Static Structure
(Contd.)

• Analyzing Subgroup Dynamics
• Track a detected subgroup over time by measuring
  the structural equivalence
• Stability
• Density and cohesion
• Euclidean distance
• Correlation coefficient
• Group activity
• The measures are computed for each time window
• Fixed A chosen time window is compared with all
  other windows
• Periodical Each time window is compared to the
  previous time window

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Evolution of Subgroups in Static Structure
Kinds of Measure-ment
Each Subgroup
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Dynamics of Communities with Fluctuating Members
(contd.)

• Clustering subgroups as a community
• Establish a graph of subgroups to denote
  similarity about them
• Similarity have been discovered as the overlap of
  members between two subgroups
• Two subgroups are similar if their overlap
  exceeds a given threshold.

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Dynamics of Communities with Fluctuating Members
(contd.)

• Visualizing the Evolution of Subgroups

Community Clustering
Control Panel
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Dynamics of Communities with Fluctuating Members
(contd.)

• Community History View

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Dynamics of Communities with Fluctuating Members
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Thank you