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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3.8

(5 reviews)

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
3.8

(5 reviews)

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

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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: Network Analysis
Category: Network Model
Category: Graph Theory
Category: Statistical Modeling
Category: Social Sciences
Category: R Programming
Category: Sociology
Category: Statistical Analysis
Category: Trend Analysis
Category: Statistical Hypothesis Testing

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: Persuasive Communication
Category: Application Programming Interface (API)
Category: Analytics
Category: Psychology
Category: Media and Communications
Category: Facebook
Category: Social Sciences
Category: Scripting
Category: Statistical Analysis
Category: Data Mining
Category: Data Analysis
Category: Sociology
Category: Network Analysis
Category: Instagram
Category: Research
Category: Behavioral Economics

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: Network Analysis
Category: Relational Databases
Category: Algebra
Category: Data Analysis
Category: Human Factors
Category: Data Visualization
Category: Innovation
Category: Data Visualization Software
Category: Data Manipulation
Category: Social Sciences

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: Natural Language Processing
Category: Unsupervised Learning
Category: Artificial Intelligence
Category: Machine Learning
Category: Text Mining
Category: Data Mining
Category: Semantic Web
Category: Statistical Analysis
Category: Applied Machine Learning
Category: Unstructured Data
Category: Analytics

Instructor

Ian McCulloh
Johns Hopkins University
17 Courses7,591 learners

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