3. Analyzing Relationships to Understand People and Groups скачать в хорошем качестве

3. Analyzing Relationships to Understand People and Groups

🎥 Part 3: Analyzing Relationships to Understand People and Groups | Network Analysis Explained** 🔗 Discover how relationships reveal insights into people, communities, and systems! Welcome to Part 3 of our Network Analysis series, where we explore how analyzing relationships—whether in social media, business, or tech—helps us better understand individuals and group dynamics. In this episode, we explore key *questions and answers* related to the power of connections and how they shape behavior, influence, and engagement. 🧠 Topics Covered in this Video: ✅ What are binary vs. valued relationships in networks? ✅ How do symmetric and asymmetric relationships affect platforms like LinkedIn, Instagram, and Twitter? ✅ Real-world examples of network analysis in airline routes, e-commerce, and social media ✅ Why directionality and weights in connections matter ✅ How to use adjacency matrices to represent complex relationships ✅ The role of centrality, clusters, and community detection in understanding influence ✅ Challenges and applications of multimode networks in universities, healthcare, and e-commerce ✅ Ethical concerns when using network data for political campaigns ✅ How Google's PageRank algorithm ranks websites using network principles ✅ A hands-on Python example using NetworkX to compute PageRank 🔍 Who is this for? This video is perfect for: ✔️ Students and researchers in social sciences, business, and computer science* ✔️ Anyone curious about how social networks work behind the scenes ✔️ Data analysts, marketers, and strategists looking to apply network insights Follow me on Telegram for more updates & notes:- https://t.me/bscit #NetworkAnalysis #SocialNetworks #PageRank #PythonNetworkX #BinaryValuedRelationships #SNA #DataScience #MachineLearning #SocialMediaStrategy #GraphTheory #Gephi #LinkedIn #TwitterAnalysis