When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Social Network Analysis

Sparen Sie mit 40% Rabatt auf 3 Monate Coursera Plus bei den Fähigkeiten, die Sie zum Strahlen bringen. Jetzt sparen

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen. Sehen Sie sich die Sprachen an, die wir anbieten.

Social Network Analysis

Dieser Kurs ist Teil mehrerer Programme.

Dozent: Ian McCulloh

2.763 bereits angemeldet

Bei enthalten

Mehr erfahren

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

11 Bewertungen

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

11 Bewertungen

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Learn to calculate and interpret key centrality measures to identify influential nodes in social networks.
Gain skills in applying statistical models to analyze relationships and dynamics within social networks.
Understand how foundational social theories inform network analysis and shape interpretations of social interactions.

Kompetenzen, die Sie erwerben

Kategorie: Statistical Analysis
Kategorie: Sociology
Kategorie: Statistical Modeling
Kategorie: Network Analysis
Kategorie: Social Sciences
Kategorie: Graph Theory
Kategorie: Statistical Hypothesis Testing
Kategorie: Network Model
Kategorie: Social Network Analysis
Kategorie: Statistical Methods
Kategorie: Dependency Analysis

Werkzeuge, die Sie lernen werden

Kategorie: R Programming
Kategorie: R (Software)
Kategorie: Statistical Software

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Bewertungen

9 Aufgaben

Unterrichtet in Englisch

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

Weitere Informationen zu Coursera für Unternehmen

Logos von Petrobras, TATA, Danone, Capgemini, P&G und L'Oreal

Erweitern Sie Ihre Fachkenntnisse

Dieser Kurs ist als Teil verfügbar

Wenn Sie sich für diesen Kurs anmelden, müssen Sie auch ein bestimmtes Programm auswählen.

Lernen Sie neue Konzepte von Branchenexperten
Gewinnen Sie ein Grundverständnis bestimmter Themen oder Tools
Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
Erwerben Sie ein Berufszertifikat zur Vorlage

In diesem Kurs gibt es 4 Module

The "Social Network Analysis" course offers a comprehensive exploration of the intricate relationships within social networks, emphasizing the theoretical and practical applications of network analysis. Through engaging modules, learners will delve into advanced topics in graph theory, centrality measures, and statistical modeling, equipping them with the skills to analyze and interpret social structures effectively.

By completing this course, learners will gain a solid understanding of how to identify key influencers, measure network cohesion, and conduct hypothesis testing using empirical data. What sets this course apart is its blend of theoretical foundations and hands-on experience using R programming for network analysis, specifically with tools like 'statnet' and 'RSiena.' Whether you’re looking to enhance your skills in data analysis or seeking to understand the dynamics of social behavior, this course will serve as a vital resource. With a focus on real-world applications, learners will emerge equipped to tackle complex social phenomena, making significant contributions to their fields.

Moduldetails

This course explores the intersection of social theories and statistical analysis within social networks, focusing on structural dependence and its implications. You will engage in hypothesis testing of social forces using empirical data, and will learn to construct networks and model longitudinal behavior with tools such as 'statnet' and 'RSiena.' Key terminology and the hierarchy of social link formation will be emphasized, alongside practical calculations of fundamental graph and network measures like Density and Degree. Additionally, you will be able to differentiate between various network types and centrality measures, equipping them with a comprehensive understanding of social network analysis.

Das ist alles enthalten

1 Lektüre1 Plug-in

In this module, you will explore advanced topics in graph theory and centrality measures as applied to social networks. You will learn to identify key influencers, measure network cohesion, and strategize interventions based on network structure and dynamics.

Das ist alles enthalten

6 Videos1 Lektüre3 Aufgaben1 Unbewertetes Labor

6 VideosInsgesamt 77 Minuten

Terminology24 Minuten
Degree Centrality17 Minuten
Betweenness Centrality14 Minuten
Closeness Centrality7 Minuten
Centrality PE8 Minuten
Graph Level Measures7 Minuten

1 LektüreInsgesamt 10 Minuten

Reading References10 Minuten

3 AufgabenInsgesamt 90 Minuten

Graph Theory and Centrality Measures60 Minuten
Introduction to Graph Theory and Network Types18 Minuten
Centrality Measures in Social Networks12 Minuten

1 Unbewertetes LaborInsgesamt 60 Minuten

Practice Lab: Graph Theory & Centrality Measures60 Minuten

In this module, you will explore Graph Theory and Centrality Measures, delving into the dynamics of social networks. You will also learn to distinguish between the six social forces and understand the hierarchical formation of social links. You will discuss foundational social theories that underpin social network analysis, providing insights into how these theories shape organizational networks and societal interactions. This module equips you with essential knowledge to analyze and interpret the intricate relationships within social structures.

Das ist alles enthalten

4 Videos2 Lektüren3 Aufgaben1 Unbewertetes Labor

4 VideosInsgesamt 79 Minuten

Social Theory Part 1 27 Minuten
Social Theory Part 230 Minuten
Social Theory Part 310 Minuten
Organizational Theories12 Minuten

2 LektürenInsgesamt 55 Minuten

Reading References15 Minuten
Self-Reflective Reading: Looking Glass Self40 Minuten

3 AufgabenInsgesamt 90 Minuten

Centralization and Social Theory60 Minuten
Understanding Social Forces and Link Formation12 Minuten
Social Theories and Organizational Networks18 Minuten

1 Unbewertetes LaborInsgesamt 60 Minuten

Practice Lab: Social Network Analysis Using R60 Minuten

In this module, you will explore Network Statistical Methods through a comprehensive study of structural dependence and its impact on statistical analysis. You will also learn to calculate link likelihoods manually and conduct hypothesis testing on social forces using empirical data. You will also gain practical skills in constructing Exponential Random Graph Models (ERGM) using ‘statnet’ in R and modeling longitudinal network behavior with Stochastic Actor Oriented Models (SAOM) using ‘RSiena’.