1 / 15

Cliques and Sub-groups

Cliques and Sub-groups. 王一 棉 1201211788. Contents. Top-down approaches Components Blocks and cut-points Lambda sets and bridges Bottom-up approaches K -cliques K-clans K- plexes K-cores Application & Thinking. Review. SNA (Social Network Analysis) Individual level

charo
Télécharger la présentation

Cliques and Sub-groups

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Cliques and Sub-groups 王一棉 1201211788

  2. Contents • Top-down approaches • Components • Blocks and cut-points • Lambda sets and bridges • Bottom-up approaches • K-cliques • K-clans • K-plexes • K-cores • Application & Thinking

  3. Review • SNA (Social Network Analysis) • Individual level • Centrality (Degree/closeness/betweenness) • Today: Group level • Clique & sub-groups level • Top-down approaches • Bottom-up approaches

  4. 今天我们聊聊帮派…… • 物以类聚，人以群分 • 拉帮结派，结党营私

  5. 江湖太乱……

  6. Top-down Components • Components of a graph are sub-graphs that are connected within, but disconnected between sub-graphs. Weak Components • Connected, regardless of the direction of ties. Strong Components • Directed path from A to B in order for the two to be in the same component.

  7. Top-down: Blocks and cut-points The UCINET algorithm Network>Regions>Bi-Component locates and identifies blocks and cutpoints.

  8. Top-down: Lambda sets and bridges • Network>Subgroups>Lambda Setlocates the vulnerable "bridges" between pairs of actors.

  9. Bottom-up: K-Cliques • precise than the general notion of a high local density. • Cliques and K-Cliques • Formally, a clique is the maximum number of actors who have all possible ties present among themselves. • K-Cliques: "a friend of a friend."

  10. Bottom-up: K-clans • A restricted version of K-cliques A B C E D F

  11. Bottom-up: K-plexes • Vulnerability in K-cliques • K-plexes • Actors may be members of a clique even if they have ties to all but k other members. • Which also means, each actor’s degree is not less than n-k 1 2 4 A 3 F C B 3-cliques, but not a 3-plexes E D

  12. Comparison • Rather than the large and "stringy" groupings sometimes produced by n-clique analysis, k-plex analysis tends to find relatively large numbers of smaller groupings. • Why? Rule (indirect or direct connection)

  13. Summary • Component • Weak: new information • Strong: information effectiveness • K-clique • In-group homogeneity • Similarity, acceptability • K-plexes • Small group • Interaction, information effectiveness

  14. Application in marketing • Combine both individual level and group level • For virus marketing, find the cut-point or bridge • For WOM, initiate it inside a small clique or strong components

  15. THANK YOU!

More Related