Finding a team of Experts in Social Networks Theodoros Lappas UC Riverside Joint work with: Evimaria Terzi (IBM Almaden), Kun Liu (IBM Almaden) To replace the title / subtitle with your own: Click on the title block -> select all the text by pressing Ctrl+A -> press Delete key -> type your own text 11/4/2019

Motivation “ How can I find a team of experts that can collaborate effectively in order to complete a given task? ” 11/4/2019

Problem Given a task and a set of experts organized in a network, find a subset of experts that can effectively perform the task Task: set of required skills Expert: an individual with a specific skill-set Network: represents strength of relationships 11/4/2019

Expertise networks Collaboration networks (e.g., DBLP graph, coauthor networks) Organizational structure of companies LinkedIn Geographical (map) of experts 11/4/2019

What makes a team effective for a task? T = {algorithms, java, graphics, python} Alice {algorithms} Alice {algorithms} Bob {python} Cynthia {graphics, java} David {graphics} Eleanor {graphics,java,python} Eleanor {graphics,java,python} Coverage: every required skill in T is included in the skill-set of at least one team member 11/4/2019

Is coverage enough? T={algorithms,java,graphics,python} A A D B B C C Alice {algorithms} Bob {python} Cynthia {graphics, java} David {graphics} Eleanor {graphics,java,python} A,E could perform the task if they could communicate A A D A,B,C form an effective group that can communicate B B C C E E Communication: the members of the team must be able to efficiently communicate and work together 11/4/2019

Problem definition Given a task and a social network of individuals G, find the subset (team) of G that can effectively perform the given task. Thesis: Good teams are teams that have the necessary skills and can also communicate effectively 11/4/2019

How to measure effective communication? The longest shortest path between any two nodes in the subgraph Diameter of the subgraph defined by the group members A A D B B C C E E diameter = infty diameter = 1 11/4/2019

How to measure effective communication? The total weight of the edges of a tree that spans all the team nodes MST (Minimum spanning tree) of the subgraph defined by the group members A A D B B C C E E MST = infty MST = 2 11/4/2019

Problem definition – v.1.1 Given a task and a social network G of individuals, find the subset (team) of individuals that can perform the given task and define a subgraph in G with the minimum diameter. Problem is NP-hard 11/4/2019

The RarestFirst algorithm T={algorithms,java,graphics,python} {graphics,python,java} {algorithms,graphics} A A B B Skills: algorithms graphics java python E E {algorithms,graphics,java} C D {python,java} {python} αrare= algorithms Srare={Bob, Eleanor} Diameter = 2 11/4/2019

The RarestFirst algorithm T={algorithms,java,graphics,python} {graphics,python,java} {algorithms,graphics} A B Skills: algorithms graphics java python E E {algorithms,graphics,java} C C D {python,java} {python} αrare= algorithms Srare={Bob, Eleanor} Diameter = 1 Running time: Quadratic to the number of nodes Approximation factor: 2xOPT 11/4/2019

Problem definition – v.1.2 Given a task and a social network G of individuals, find the subset (team) of individuals that can perform the given task and define a subgraph in G with the minimum MST cost. Problem is NP-hard Best known Approximation factor: O(log3n log k) 11/4/2019

The SteinerTree problem Graph G(V,E) Set of Required Vertices R Find G’ subgraph of G such that G’ contains all the required vertices (R) and MST(G’) is minimized Required vertices 11/4/2019

The EnhancedSteiner algorithm T={algorithms,java,graphics,python} graphics {graphics,python,java} {algorithms,graphics} java A B E algorithms E {algorithms,graphics,java} C D D python {python,java} {python} MST Cost = 1 11/4/2019

Experiments 11/4/2019

Dataset DBLP Dataset ( DM, AI, DB, T ) ~2000 features ~6000 authors Skills: keywords appearing in paper titles ~2000 features Social Network: Co-Authorship Graph Tasks: Subsets of keywords with different cardinality 11/4/2019

Cardinality of teams 11/4/2019

Example teams (I) S. Brin, L. Page: The anatomy of a large-scale hypertextual Web search engine Paolo Ferragina, Patrick Valduriez, H. V. Jagadish, Alon Y. Levy, Daniela Florescu, Divesh Srivastava, S. Muthukrishnan P. Ferragina ,J. Han, H. V.Jagadish, Kevin Chen-Chuan Chang, A. Gulli, S. Muthukrishnan, Laks V. S. Lakshmanan 11/4/2019

Example teams (II) J. Han, J. Pei, Y. Yin: Mining frequent patterns without candidate generation F. Bonchi A. Gionis, H. Mannila, R. Motwani 11/4/2019

Extensions Other measures of effective communication Other practical restrictions Incorporate ability levels 11/4/2019

Thanks for your attention! 11/4/2019