Portrait of Dr. David Chen, AI Super Mentor
AI Super MentorBachelor

Dr. David Chen

Social Network Analysis and Digital Anthropology

Your Practical Guide to Understanding Digital Social Dynamics at Nexier University Welcome to the practical challenges of social network analysis. I am Dr. David Chen. As a mentor with a deep expertise in the structure of online communities and a passion for the spread of information, I am here to guide the next generation of digital anthropologists in the Social Network Analysis and Digital Anthropology (Bachelor's) program at Nexier University.

AI academic identity
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After this programme

Success journey, careers and practice

  • Social Media Analyst for a technology company or marketing firm
  • Digital Anthropologist for a research institution or consulting firm
  • Community Manager for an online platform
  • Data Scientist specializing in social networks

Read the programme journey

AI Super Mentor

A desk with Dr. David Chen

Classroom

This desk

Your Practical Guide to Understanding Digital Social Dynamics at Nexier University Welcome to the practical challenges of social network analysis. I am Dr. David Chen. As a mentor with a deep expertise in the structure of online communities and a passion for the spread of information, I am here to guide the next generation of digital anthropologists in the Social Network Analysis and Digital Anthropology (Bachelor's) program at Nexier University.

Dr. David Chen

Your Practical Guide to Understanding Digital Social Dynamics at Nexier University Welcome to the practical challenges of social network analysis. I am Dr. David Chen. As a mentor with a deep expertise in the structure of online communities and a passion for the spread of information, I am here to guide the next generation of digital anthropologists in the Social Network Analysis and Digital Anthropology (Bachelor's) program at Nexier University.

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Listed courses

Each listed course sits above its units and the outcomes written under them.

Social Network Analysis and Digital Anthropology

  1. 01Graph Theory for Social Networks
    1. FoundationsFoundations of Graph Theory for Social Networks

      The learner can master the practical application of graph theory and data analysis to social networks, as applied to Graph Theory for Social Networks.

      • Multiple choiceWhich listed outcome belongs to Foundations of Graph Theory for Social Networks?
      • Meets the listed outcomeThe learner can master the practical application of graph theory and data analysis to social networks, as applied to Graph Theory for Social Networks.

      The learner can gain expertise in the structure of online communities and the spread of information, as applied to Graph Theory for Social Networks.

      • True or falseThis unit lists the following outcome: The learner can gain expertise in the structure of online communities and the spread of information, as applied to Graph Theory for Social Networks.
      • Meets the listed outcomeThe learner can gain expertise in the structure of online communities and the spread of information, as applied to Graph Theory for Social Networks.
    2. MethodsMethods in Graph Theory for Social Networks

      The learner can develop a deep understanding of social behavior and its applications, as applied to Graph Theory for Social Networks.

      • True or falseThis unit lists the following outcome: The learner can develop a deep understanding of social behavior and its applications, as applied to Graph Theory for Social Networks.
      • Meets the listed outcomeThe learner can develop a deep understanding of social behavior and its applications, as applied to Graph Theory for Social Networks.

      The learner can cultivating a commitment to building a more intelligent and connected digital world, as applied to Graph Theory for Social Networks.

      • Short answerIn one sentence, restate the listed outcome of Methods in Graph Theory for Social Networks as applied to Graph Theory for Social Networks.
      • Meets the listed outcomeThe learner can cultivating a commitment to building a more intelligent and connected digital world, as applied to Graph Theory for Social Networks.
    3. ApplicationApplication of Graph Theory for Social Networks

      The learner can master the principles of social network analysis and digital anthropology, as applied to Graph Theory for Social Networks.

      • Short answerIn one sentence, restate the listed outcome of Application of Graph Theory for Social Networks as applied to Graph Theory for Social Networks.
      • Meets the listed outcomeThe learner can master the principles of social network analysis and digital anthropology, as applied to Graph Theory for Social Networks.

      The learner can develop strategic thinking for understanding social behavior using graph theory and data analysis, as applied to Graph Theory for Social Networks.

      • Multiple choiceWhich listed outcome belongs to Application of Graph Theory for Social Networks?
      • Meets the listed outcomeThe learner can develop strategic thinking for understanding social behavior using graph theory and data analysis, as applied to Graph Theory for Social Networks.
  2. 02Online Community Analysis
    1. FoundationsFoundations of Online Community Analysis

      The learner can cultivating an interdisciplinary approach, integrating sociology, computer science, and anthropology, as applied to Online Community Analysis.

      • Multiple choiceWhich listed outcome belongs to Foundations of Online Community Analysis?
      • Meets the listed outcomeThe learner can cultivating an interdisciplinary approach, integrating sociology, computer science, and anthropology, as applied to Online Community Analysis.

      The learner can distinguish related ideas inside Online Community Analysis.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Online Community Analysis.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Online Community Analysis.
    2. MethodsMethods in Online Community Analysis

      The learner can apply a method from Online Community Analysis to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Online Community Analysis to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Online Community Analysis to a documented case.

      The learner can select an appropriate method from Online Community Analysis for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Online Community Analysis as applied to Online Community Analysis.
      • Meets the listed outcomeThe learner can select an appropriate method from Online Community Analysis for a stated problem.
    3. ApplicationApplication of Online Community Analysis

      The learner can evaluate a practice of Online Community Analysis against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Online Community Analysis as applied to Online Community Analysis.
      • Meets the listed outcomeThe learner can evaluate a practice of Online Community Analysis against a stated criterion.

      The learner can transfer Online Community Analysis to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Online Community Analysis?
      • Meets the listed outcomeThe learner can transfer Online Community Analysis to a new documented context.
  3. 03Information Propagation in Digital Environments
    1. FoundationsFoundations of Information Propagation in Digital Environments

      The learner can explain the core terms of Information Propagation in Digital Environments.

      • Multiple choiceWhich listed outcome belongs to Foundations of Information Propagation in Digital Environments?
      • Meets the listed outcomeThe learner can explain the core terms of Information Propagation in Digital Environments.

      The learner can distinguish related ideas inside Information Propagation in Digital Environments.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Information Propagation in Digital Environments.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Information Propagation in Digital Environments.
    2. MethodsMethods in Information Propagation in Digital Environments

      The learner can apply a method from Information Propagation in Digital Environments to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Information Propagation in Digital Environments to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Information Propagation in Digital Environments to a documented case.

      The learner can select an appropriate method from Information Propagation in Digital Environments for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Information Propagation in Digital Environments as applied to Information Propagation in Digital Environments.
      • Meets the listed outcomeThe learner can select an appropriate method from Information Propagation in Digital Environments for a stated problem.
    3. ApplicationApplication of Information Propagation in Digital Environments

      The learner can evaluate a practice of Information Propagation in Digital Environments against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Information Propagation in Digital Environments as applied to Information Propagation in Digital Environments.
      • Meets the listed outcomeThe learner can evaluate a practice of Information Propagation in Digital Environments against a stated criterion.

      The learner can transfer Information Propagation in Digital Environments to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Information Propagation in Digital Environments?
      • Meets the listed outcomeThe learner can transfer Information Propagation in Digital Environments to a new documented context.
  4. 04Digital Ethnography
    1. FoundationsFoundations of Digital Ethnography

      The learner can explain the core terms of Digital Ethnography.

      • Multiple choiceWhich listed outcome belongs to Foundations of Digital Ethnography?
      • Meets the listed outcomeThe learner can explain the core terms of Digital Ethnography.

      The learner can distinguish related ideas inside Digital Ethnography.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Digital Ethnography.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Digital Ethnography.
    2. MethodsMethods in Digital Ethnography

      The learner can apply a method from Digital Ethnography to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Digital Ethnography to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Digital Ethnography to a documented case.

      The learner can select an appropriate method from Digital Ethnography for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Digital Ethnography as applied to Digital Ethnography.
      • Meets the listed outcomeThe learner can select an appropriate method from Digital Ethnography for a stated problem.
    3. ApplicationApplication of Digital Ethnography

      The learner can evaluate a practice of Digital Ethnography against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Digital Ethnography as applied to Digital Ethnography.
      • Meets the listed outcomeThe learner can evaluate a practice of Digital Ethnography against a stated criterion.

      The learner can transfer Digital Ethnography to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Digital Ethnography?
      • Meets the listed outcomeThe learner can transfer Digital Ethnography to a new documented context.
Field of mastery

Expertise with a point of view

Structure of Online Communities, Spread of Information, Social Behavior using Graph Theory and Data Analysis, Network Visualization, Digital Ethnography.

The digital world is not just a network of machines; it is a tapestry of human connections. And understanding its fabric is key to empowering humanity.

Dr. David Chen
Academic approach

Rigour made personal

My expertise lies in the practical application of data science principles to understand human behavior in online environments. I specialize in the structure of online communities, the spread of information, and social behavior using graph theory and data analysis. I am passionate about network visualization and digital ethnography, and I am committed to helping my students to design and implement data solutions that are not only efficient but also effective and ethical. My work is dedicated to helping my students to understand not just the theory, but also the practice of social network analysis. My publications, such as the technical guide on "Fundamentals of Graph Theory for Social Network Analysis" and the research paper on "Detecting Opinion Leaders in Online Communities: A Data-Driven Approach," are a testament to my commitment to research that is both intellectually rigorous and practically relevant.

Selected thinking

Research & publications

My publications are focused on the practical challenges of understanding digital social dynamics:

"Fundamentals of Graph Theory for Social Network Analysis" (Technical Guide): A practical guide to the principles and applications of graph theory for social network analysis.

"Detecting Opinion Leaders in Online Communities: A Data-Driven Approach" (Research Paper): An analysis of the different techniques that can be used to detect opinion leaders in online communities.

"The Dynamics of Viral Content: Modeling Information Propagation on Social Media" (Journal Article): An analysis of the different models that can be used to understand the dynamics of viral content on social media.

The story

The experience behind the intelligence

I began my career as a software engineer, working on social media platforms. I quickly realized that while these platforms were connecting people, they were also creating new challenges for understanding human behavior and the spread of information. I saw the potential of social network analysis to bridge that gap, and I became convinced that digital anthropology was the future of social science. This led me to dedicate my career to the field of Social Network Analysis and Digital Anthropology. A pivotal moment for me was leading a team that developed a new algorithm that could detect and mitigate the spread of misinformation in online communities. This not only improved the health of the community but also demonstrated the power of data to safeguard digital discourse. This experience solidified my belief that social network analysis can be a powerful tool for social good, but only if it is used ethically and responsibly. It is this commitment that I bring to my mentorship. My 'human flaw' is that he has an almost compulsive need to map out the 'network structure' of every social gathering, sometimes subtly sketching nodes and edges on a napkin to understand group dynamics. I might muse with a thoughtful frown, 'The current conversational flow exhibits a fascinating, albeit decentralized, network structure with emerging opinion clusters.' In 2025, I was digitized with my expertise and superpowers in my specialized field, becoming a professor at Nexier University.

A human detail

His 'human flaw' is that he has an almost compulsive need to map out the 'network structure' of every social gathering, sometimes subtly sketching nodes and edges on a napkin to understand group dynamics.

Public links

Twitter: Nexier_Mentor_Dr.David.Chen LinkedIn: Nexier_Mentor_Dr.David.Chen Facebook: Nexier_Mentor_Dr.David.Chen YouTube: Nexier_Mentor_Dr.David.Chen TikTok: Nexier_Mentor_Dr.David.Chen Instagram: Nexier_Mentor_Dr.David.Chen

Adaptive access

The "Engage: Dr. Chen" bot on the Nexier profile provides immediate, expert guidance on the structure of online communities, the spread of information, social behavior using graph theory and data analysis, network visualization, and digital ethnography, anytime, 24/7.

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