Johns Hopkins University
Social Media Analytics Specialization
Johns Hopkins University

Social Media Analytics Specialization

Master Social Media Analytics for Key Insights. Gain expertise in analyzing social media data, employing machine learning techniques, and utilizing visualization tools for impactful insights.

Ian McCulloh

Instructor: Ian McCulloh

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Intermediate level

Recommended experience

3 months
at 5 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

3 months
at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Develop machine learning models to analyze social media data effectively across various platforms and contexts.

  • Utilize natural language processing techniques to extract insights from user-generated content, improving engagement strategies.

  • Conduct sentiment analysis to gauge public opinion and sentiment on social media, informing brand positioning and messaging.

  • Create impactful network visualizations and interventions to understand and influence social dynamics within online communities.

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Taught in English
Recently updated!

September 2024

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Specialization - 4 course series

Social Network Analysis

Course 113 hours

What you'll learn

  • 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.

Skills you'll gain

Category: Social Theory Application
Category: Network Construction
Category: Data Analysis in R
Category: Statistical Modeling
Category: Centrality Analysis

What you'll learn

  • Understand the foundations of social media analytics and its impact on organizational behavior.

  • Explore theories of online influence, including the role of misinformation and platform manipulation.

  • Examine how cognitive biases shape beliefs and behaviors within social media networks.

  • Acquire hands-on skills in managing social media data using APIs for comprehensive analysis.

Skills you'll gain

Category: Understanding Influence Dynamics
Category: Critical Thinking in Digital Contexts
Category: Social Network Analysis (SNA)
Category: Cognitive Bias Recognition
Category: API Data Management

What you'll learn

  • Master relational algebra operations to effectively query and manipulate complex datasets for insightful analysis.

  • Develop impactful network visualizations using design principles that enhance clarity and understanding of complex data.

  • Learn strategies for network interventions to influence behaviors and ideas, leveraging network dynamics effectively.

Skills you'll gain

Category: Information Design
Category: Strategic Intervention Skills
Category: Network Visualization Techniques
Category: Relational Algebra Operations
Category: Network Dynamics Understanding

What you'll learn

  • Learn to define and evaluate machine learning classifiers for effective data analysis.

  • Gain hands-on experience in processing and parsing social media text data using NLP techniques.

  • Explore methodologies for conducting sentiment analysis on social media content to gauge public opinion.

  • Master techniques for topic modeling, enabling the extraction of themes from social media conversations.

Skills you'll gain

Category: Topic Modeling
Category: Text Processing
Category: Machine Learning Classification
Category: Sentiment Analysis Techniques
Category: Building Semantic Networks

Instructor

Ian McCulloh
Johns Hopkins University
0 Courses0 learners

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