Social Network Analy week1

Introduction to Social Network Analysis

  • Social network analysis combines multiple fields: business, social sciences, economics.

  • Led by Valentin Danchoev, lecturer in business analytics.

  • Structure of the module will include lectures and seminars.

QM Plus Web Page Overview

  • Module outline available on QM Plus.

  • Contains module description, aims, weekly topics, and reading material.

  • Example topic for week 2: network code subset measures for seminar preparation.

  • Access to required literature through provided links.

Lectures and Seminars

  • Three seminars scheduled during the semester:

    • 1 immediately after the lecture.

    • 2 on Tuesday (3 PM and 5 PM).

  • Assessment breakdown:

    • Midterm test after week 7 (scheduled in week 8).

    • Research project (2,000 words), optional group work (2-4 members) or individually.

Topics Covered in Social Network Analysis

  • Introduction to Social Network Analysis: Definition and importance.

  • Basic Concepts of Network Science: Types of networks, measures, properties, and applications in business and social networks.

  • Weak Ties: Importance in job hunting and innovation support in companies.

  • Blockage Structures: Missing connections in networks and their implications.

  • Social Influences and Homophily: Tendency of individuals to connect with similar others.

  • Cascades and Diffusion: How information spreads through networks, including misinformation.

  • Echo Chambers in Media: Effect of network structures on information sharing and cultural impacts.

Methodology of Social Network Analysis

  • Focus on interconnections rather than individual attributes.

  • Importance of analyzing networks through attributes (demographics) and their interactions.

Recommended Textbooks

  • "A First Course in Network Science" - foundational text, Python coding elements included (not required).

  • "Networks, Crowds, and Markets" - conceptual insights and literature from varied sources.

  • Mark Newman’s Textbook - influential works in social network analysis.

  • General expectation: Participation, critical evaluation, engagement, and preparation for lectures.

Research Project

  • Topics must relate to theories and methods discussed in the course.

  • Emphasis on using social network analysis to address business issues.

Understanding Networks

  • Definition of Networks: Consists of points (nodes) connected by edges (relationships).

  • Types of Edges:

    • Directed Edges: Show direction (e.g. advice giving).

    • Undirected Edges: No direction necessary (e.g. friendships).

  • Weights: Quantify strength or frequency of relationships (e.g. frequency of emails or monetary transactions).

Types of Networks

  • Social Networks: Represent partnerships, friendships, etc.

  • Economic Networks: Connection between organizations or individuals.

  • Technological Networks: Infrastructure links (e.g. Internet connections).

  • Biological Networks: Interactions among biological entities.

  • Informational Networks: Links among webpages, knowledge systems (e.g. Wikipedia).

Social Dynamics and Networks

  • Example: Conflict within social groups and its impact on network structure.

  • Segregation patterns observed among different demographics in social contexts (e.g., genders in schools).

Case Studies in Networks

  • Historical examples of social-economic networks (e.g. familial ties in medieval France).

  • Analysis of networks within educational settings, romantic relationships, and social media.

Importance of Network Analysis

  • Helps decipher complex connections within various systems.

  • Application in predicting outcomes, disease spread, and social influence.

  • Potential impact of network structure on professionals (e.g., job opportunities for network analysts).

Network Properties

  • Exploration of different network structures to understand underlying patterns and dynamics.

  • The notion of centralities illustrating the significance of individual nodes in networks.

Applications of Network Analysis

  • Disease Transmission: Identify how diseases spread within connected communities.

  • Advertising and Viral Trends: Understand spread patterns of information and cultural trends.

  • Expert Interaction: How professionals adopt practices based on their network connections.

  • Insights into communication patterns within organizations for improved strategies.