Overview
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This specialization is designed for post-graduate students aiming to develop advanced skills in social media analytics and its practical applications. Through four comprehensive courses, learners will explore key topics such as machine learning, natural language processing, sentiment analysis, and network analysis, equipping them to analyze complex social media data and derive actionable insights. By mastering data manipulation techniques and effective visualization tools, students will be prepared to influence consumer behavior and enhance digital marketing strategies. Collaborating with industry partners, the specialization emphasizes real-world applications, enabling students to navigate the evolving landscape of social media analytics effectively. Upon completion, learners will possess the expertise needed to leverage analytics for informed decision-making, drive impactful results, and elevate their careers in the dynamic field of digital communication. This specialization will empower you with the knowledge and skills to make data-driven decisions, making you a valuable asset in any organization.
Syllabus
Course 1: Social Network Analysis
- Offered by Johns Hopkins University. The "Social Network Analysis" course offers a comprehensive exploration of the intricate relationships ... Enroll for free.
Course 2: Online Influence and Persuasion
- Offered by Johns Hopkins University. In the "Online Influence and Persuasion" course, learners will explore the intricate dynamics of social ... Enroll for free.
Course 3: Network Visualization and Intervention
- Offered by Johns Hopkins University. In the "Network Interventions" course, learners will explore the foundational principles of data ... Enroll for free.
Course 4: Artificial Intelligence in Social Media Analytics
- Offered by Johns Hopkins University. In the course "Artificial Intelligence in Social Media Analytics", learners will explore the ... Enroll for free.
- Offered by Johns Hopkins University. The "Social Network Analysis" course offers a comprehensive exploration of the intricate relationships ... Enroll for free.
Course 2: Online Influence and Persuasion
- Offered by Johns Hopkins University. In the "Online Influence and Persuasion" course, learners will explore the intricate dynamics of social ... Enroll for free.
Course 3: Network Visualization and Intervention
- Offered by Johns Hopkins University. In the "Network Interventions" course, learners will explore the foundational principles of data ... Enroll for free.
Course 4: Artificial Intelligence in Social Media Analytics
- Offered by Johns Hopkins University. In the course "Artificial Intelligence in Social Media Analytics", learners will explore the ... Enroll for free.
Courses
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In the course "Artificial Intelligence in Social Media Analytics", learners will explore the intersection of artificial intelligence and social media analytics, equipping them with essential skills to navigate and analyze digital landscapes. By delving into machine learning fundamentals, natural language processing, sentiment analysis, and topic modeling, participants will gain practical experience in applying AI techniques to real-world social media data. This course stands out by providing not only theoretical insights but also hands-on opportunities to construct classifiers, perform sentiment analysis, and build semantic networks, all tailored to the complexities of social media content. As learners progress, they will develop a keen understanding of how AI can uncover hidden patterns, sentiment, and topics within vast amounts of unstructured data. The unique blend of foundational concepts and practical applications ensures that participants can effectively analyze social media interactions and derive actionable insights. Whether for career advancement or personal interest, this course offers a comprehensive toolkit to leverage AI for understanding social dynamics and enhancing engagement strategies in digital platforms.
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In the "Network Interventions" course, learners will explore the foundational principles of data manipulation, visualization, and the dynamics of networks. This course stands out by seamlessly integrating theoretical knowledge with practical applications. You'll gain expertise in Relational Algebra, empowering you to construct and interpret operations that effectively manage complex datasets. The course also emphasizes the art of Network Visualization, where you will learn to create impactful visual representations of data, making complex information accessible and understandable. Additionally, the course delves into Network Interventions, teaching you how to influence behaviors and ideas within social networks. You will master strategies to identify opinion leaders and implement effective segmentation techniques, essential skills for driving change in various contexts. By the end of the course, you will be equipped not only with analytical and visualization skills but also with the ability to influence social dynamics, preparing you for impactful roles in data-driven environments. This unique combination of skills makes the Network Intervention course an invaluable asset for those looking to thrive in the evolving landscape of data science and social network analysis.
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In the "Online Influence and Persuasion" course, learners will explore the intricate dynamics of social media through the lens of Social Network Analysis (SNA). This course is designed to equip you with essential skills to analyze how social media influences behaviors, perceptions, and organizational structures. By mastering key SNA measures and clustering techniques, you will uncover valuable insights into network subgroups and social forces. What sets this course apart is its comprehensive approach to understanding online influence, including the neurobiological aspects of social media addiction and the interplay between misinformation and persuasion. You will gain hands-on experience managing social media data through APIs, enabling you to extract, transform, and analyze data effectively. By the end of this course, you will not only understand the theoretical foundations of online influence and persuasion but also acquire practical skills that can be applied in various contexts, from marketing to behavioral research. This unique combination of theory and practice will prepare you to navigate the complexities of the digital landscape and make data-driven decisions that can enhance organizational effectiveness.
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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.
Taught by
Ian McCulloh