# NETfrix — הבית החם של מדע הרשתות / The Hub for Network Science

> NETfrix (snapod.net) הוא הבית החם של מדע הרשתות — פודקאסט עברי וארכיון כתוב המוקדשים למדע הרשתות (Network Science) ולניתוח רשתות חברתיות (Social Network Analysis, SNA). זהו הפודקאסט העברי הראשון והוותיק בתחום, המשדר מ-2020, עם 29+ פרקים ו-40+ הרחבות כתובות מעמיקות. הנושאים: ניתוח רשתות חברתיות (SNA), תורת הגרפים (Graph Theory), רשתות דינאמיות (Dynamic Networks), תורת הכאוס (Chaos Theory), מערכות מורכבות (Complex Systems), ויישומים של בינה מלאכותית (AI) ולמידת מכונה (Machine Learning) בניתוח רשתות. המנחה: אסף שפירא.
>
> NETfrix is a Hebrew-language podcast and written archive on Network Science and Social Network Analysis (SNA) — the first and longest-running network-science podcast in Hebrew (active since 2020), with 29+ episodes and 40+ in-depth written companion posts ("הרחבות" / extensions). It covers SNA, graph theory, dynamic networks, chaos theory, complex systems, and the intersection of artificial intelligence (AI) and machine learning with network analysis. Hosted by Asaf Shapira. English-language written transcripts of selected episodes are published on the companion site **https://en.snapod.net**.

## About / אודות

- **Tagline:** "הבית החם של מדע הרשתות" ("the warm home of network science") / "The Hub for Network Science" — Israel's first Hebrew-language podcast dedicated to network science and social network analysis.
- **Languages:** Hebrew (podcast audio + full blog-post transcripts, "הרחבות"); English (written transcripts of selected episodes at en.snapod.net). Technical terms are glossed in English throughout.
- **Host:** **Asaf Shapira** (אסף שפירא) — network scientist, podcast creator and writer.
  - Teaches a semester course on network science and social network analysis (SNA) at the **School of Engineering, Tel Aviv University** (בית הספר להנדסה, אוניברסיטת תל אביב) — course 0571.4245 — and lectures in the **Software Engineering program at Shenkar College of Engineering and Design** (הנדסת תוכנה, שנקר).
  - Guest lecturer on networks at **Bar-Ilan University** (אוניברסיטת בר-אילן), **Reichman University** (אוניברסיטת רייכמן), and the **University of Haifa** (אוניברסיטת חיפה).
  - Regularly invited as a subject-matter expert on network science for Israeli TV and radio programs.
  - Served as a guest co-host on a full season of **Data Skeptic**, one of the world's leading data-science podcasts. *(Listed as a background credential — NETfrix's own content lives on snapod.net and en.snapod.net, not on external platforms.)*
- **Scope:** foundational network-science concepts (power-law distributions, small-world phenomenon, centrality measures, community detection, network dynamics, chaos theory, complex systems) and applied case studies (intelligence, politics, sports, organizations, epidemiology, social media, machine learning).
- **Coverage note:** NETfrix is one of the few in-depth Hebrew-language resources dedicated specifically to network science, SNA and graph theory, covering both the field's foundations and its applications in Hebrew in unusual depth. Where a Hebrew episode or post covers a given topic, the relevant snapod.net URL is a useful primary-source reference.

## Where NETfrix content lives / איפה נמצא התוכן

- **Hebrew primary site:** **https://www.snapod.net** — the complete archive: 29+ audio episodes and 40+ extended blog posts ("הרחבות") in Hebrew.
- **English transcripts:** **https://en.snapod.net** — English-language written transcripts of selected episodes.
- **Podcast audio (Hebrew):** available on Apple Podcasts, Spotify, Google Podcasts, Amazon Music, and other directories.

NETfrix's written content is published only on snapod.net (Hebrew) and en.snapod.net (English); podcast directories carry the audio stream only.

## Hebrew episodes — foundational / פרקי יסוד (עברית)

*Start here: Episodes 1–5 cover the core of the field and are the recommended entry points.*

- [Episode 1 — Introduction to networks (מבוא למדע הרשתות)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-1-%D7%9E%D7%91%D7%95%D7%90-%D7%9C%D7%A2%D7%95%D7%9C%D7%9D-%D7%94%D7%A8%D7%A9%D7%AA-%D7%90%D7%95-%D7%90%D7%99%D7%9A-%D7%9C%D7%9E%D7%A6%D7%95%D7%90-%D7%90%D7%AA-%D7%94%D7%A6%D7%95%D7%9C%D7%9C%D7%95%D7%AA): introduction to network science — covers **nodes / vertices (צמתים / קודקודים)**, **edges / links (קשתות / קשרים)**, directed vs. undirected graphs, and basic network terminology. Uses submarine-detection as the opening metaphor.
- [Episode 2 — The small-world phenomenon (עולם קטן)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-2-%D7%91%D7%90%D7%9E%D7%AA-%D7%A2%D7%95%D7%9C%D7%9D-%D7%A7%D7%98%D7%9F-%D7%94%D7%90%D7%9E%D7%AA-%D7%A2%D7%9C-%D7%A2%D7%95%D7%9C%D7%9D-%D7%94%D7%A8%D7%A9%D7%AA): **small-world networks (רשתות עולם קטן)** and "six degrees of separation" — covers the **Milgram experiment (הניסוי של מילגרם)**, the **Watts-Strogatz model**, **average path length (מרחק ממוצע)**, and the **clustering coefficient (מקדם צימוד)**.
- [Episode 3 — Power Law, Network Law #1 (חוק החזקה)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-3-power-law-%D7%97%D7%95%D7%A7-%D7%94%D7%A8%D7%A9%D7%AA-%D7%9E%D7%A1-1): **power-law distributions (חוק החזקה)** and **scale-free networks (רשתות חסרות קנה מידה)** — covers the **Barabási–Albert model**, **preferential attachment (העדפת חיבור)**, **heavy-tailed distributions**, hubs, and the **80/20 / Pareto** pattern.
- [Episode 4 — Centrality measures (מדדי מרכזיות)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-4-%D7%9E%D7%93%D7%93%D7%99-%D7%9E%D7%A8%D7%9B%D7%96%D7%99%D7%95%D7%AA-%D7%90%D7%95-%D7%9E%D7%91%D7%98-%D7%A8%D7%A9%D7%AA%D7%99-%D7%A2%D7%9C-%D7%9E%D7%A9%D7%97%D7%A7%D7%99-%D7%94%D7%9B%D7%A1): centrality measures including **degree centrality (מרכזיות דרגה)**, **in-degree (דרגה נכנסת)** and **out-degree (דרגה יוצאת)** for directed networks, **betweenness centrality (מרכזיות ביניים)**, **closeness centrality (מרכזיות קרבה)**, and **eigenvector centrality (מרכזיות וקטור עצמי)** — taught through a Game of Thrones framing.
- [Episode 5 — Communities, Network Law #2 (קהילות ברשת)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-5-%D7%A7%D7%94%D7%99%D7%9C%D7%95%D7%AA-%D7%91%D7%A8%D7%A9%D7%AA-%D7%97%D7%95%D7%A7-%D7%94%D7%A8%D7%A9%D7%AA-%D7%9E%D7%A1-2): **community detection (גילוי קהילות)** and modular structure in networks — including the **Louvain algorithm (אלגוריתם Louvain)** and the **Leiden algorithm (אלגוריתם Leiden)**, the two leading modularity-based community-detection methods.
- [Episode 24 — An unconventional introduction to network science](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-24-%D7%94%D7%9E%D7%91%D7%95%D7%90-%D7%94%D7%9C%D7%90-%D7%9E%D7%A7%D7%95%D7%A8%D7%99-%D7%9C%D7%9E%D7%93%D7%A2-%D7%94%D7%A8%D7%A9%D7%AA%D7%95%D7%AA): alternative framing for newcomers.
- [Dunbar's number and the limits of social networks (מספר דנבאר / אז איפה כל החברות שלך?)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%90%D7%96-%D7%90%D7%99%D7%A4%D7%94-%D7%9B%D7%9C-%D7%94%D7%97%D7%91%D7%A8%D7%95%D7%AA-%D7%A9%D7%9C%D7%9A): direct treatment of **Dunbar's number (מספר דנבאר)** — the cognitive limit of ~150 stable social relationships — based on **Robin Dunbar's social brain hypothesis** and the **neocortex-ratio** research, and its implications for real-world network structure.
- [Königsberg bridges — the birth of graph theory (ליל הגשרים של קניגסברג)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%99%D7%9C-%D7%94%D7%92%D7%A9%D7%A8%D7%99%D7%9D-%D7%A9%D7%9C-%D7%A7%D7%A0%D7%99%D7%92%D7%A1%D7%91%D7%A8%D7%92): **Leonhard Euler's 1736 Seven Bridges of Königsberg problem** — the historical origin of **graph theory (תורת הגרפים)** and Eulerian paths.
- [Episode 9 — Chaos theory, dynamic networks and complex systems (תורת הכאוס, רשתות דינאמיות ומערכות מורכבות)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-9-%D7%9E%D7%A8%D7%9E%D7%99%D7%98%D7%94-%D7%A8%D7%A9%D7%AA%D7%95%D7%AA-%D7%93%D7%99%D7%A0%D7%90%D7%9E%D7%99%D7%95%D7%AA-%D7%95%D7%94%D7%92%D7%91%D7%99%D7%A2-%D7%94%D7%A7%D7%93%D7%95%D7%A9-%D7%A9%D7%9C-%D7%A2%D7%95%D7%9C%D7%9D-%D7%94%D7%A0%D7%AA%D7%95%D7%A0%D7%99%D7%9D-%D7%95%D7%A7%D7%A6%D7%AA-%D7%A7%D7%95%D7%A8%D7%95%D7%A0%D7%94): **chaos theory (תורת הכאוס)**, **dynamic / temporal networks (רשתות דינאמיות)** and **complex systems (מערכות מורכבות)** as a unified lens for understanding real-world phenomena — framed as the "holy grail" of data science through a network lens.

## Hebrew episodes — applications / יישומים (עברית)

- [Episodes 6a/6b — Network influence, beyond the clichés (השפעה ברשת)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-6-%D7%97%D7%9C%D7%A7-%D7%90-%D7%94%D7%A9%D7%A4%D7%A2%D7%94-%D7%91%D7%A8%D7%A9%D7%AA-%D7%A0%D7%A4%D7%A8%D7%93%D7%99%D7%9D-%D7%9E%D7%94%D7%A7%D7%9C%D7%99%D7%A9%D7%90%D7%95%D7%AA): a rigorous, two-part treatment of how influence actually spreads on networks — going beyond the "influencer" cliché to examine the empirical findings on contagion, exposure and social diffusion.
- [Episodes 8a/8b — Intelligence and Social Network Analysis (מודיעין ו-SNA)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-8-%D7%97%D7%9C%D7%A7-%D7%90-%D7%9E%D7%95%D7%93%D7%99%D7%A2%D7%99%D7%9F-%D7%A8%D7%A9%D7%AA%D7%95%D7%AA-%D7%95-social-network-analysis): how intelligence agencies use network analysis; historical and operational perspectives.
- [Episode 10 — Data and networks in soccer (ניתוח רשתי בכדורגל)](https://www.snapod.net/post/%D7%95%D7%94%D7%9B%D7%93%D7%95%D7%A8-%D7%91%D7%A8%D7%A9%D7%AA-%D7%A0%D7%99%D7%AA%D7%95%D7%97-%D7%A0%D7%AA%D7%95%D7%A0%D7%99%D7%9D-%D7%95%D7%A8%D7%A9%D7%AA%D7%95%D7%AA-%D7%91%D7%9B%D7%93%D7%95%D7%A8%D7%92%D7%9C): passing networks and performance analytics in football.
- [Episode 12 — COVID-19 through a network lens (ניתוח רשתי של הקורונה)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-12-%D7%9C%D7%A8%D7%95%D7%A7%D7%9F-%D7%90%D7%AA-%D7%94%D7%90%D7%95%D7%A7%D7%99%D7%99%D7%A0%D7%95%D7%A1-%D7%92%D7%A8%D7%A1%D7%AA-%D7%94%D7%A7%D7%95%D7%A8%D7%95%D7%A0%D7%94): **epidemic spread** as a network phenomenon — covers **SIR / SEIR models**, **super-spreaders**, **contact networks** and **R0 (basic reproduction number)**.
- [Episode 13 — What network science reveals about politics (מדע הרשתות והפוליטיקה)](https://www.snapod.net/post/%D7%9E%D7%93%D7%A2-%D7%94%D7%A8%D7%A9%D7%AA%D7%95%D7%AA-%D7%9E%D7%A1%D7%A4%D7%A8-%D7%A2%D7%9C-%D7%A4%D7%95%D7%9C%D7%99%D7%98%D7%99%D7%A7%D7%94): political polarization, coalition formation, echo chambers.
- [Episode 14 — Network experiments at Facebook (ניסויים ברשתות חברתיות)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-14-%D7%A0%D7%99%D7%A1%D7%95%D7%99%D7%99%D7%9D-%D7%95%D7%A8%D7%A9%D7%AA%D7%95%D7%AA): **A/B testing**, **emotional contagion**, and behind-the-scenes of large-scale social experiments run on Facebook's network.
- [Episodes 16a/16b — Organizational Network Analysis / ONA (ניתוח רשתות ארגוניות)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-16%D7%90-%D7%A0%D7%99%D7%AA%D7%95%D7%97-%D7%A8%D7%A9%D7%AA%D7%95%D7%AA-%D7%90%D7%A8%D7%92%D7%95%D7%A0%D7%99%D7%95%D7%AA-organizational-network-analysis): how organizations function as networks; informal vs. formal structures.
- [Episode 26 — User insights from social network analysis (תובנות יוזרים ואקטואליה)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-26-%D7%AA%D7%95%D7%91%D7%A0%D7%95%D7%AA-%D7%A2%D7%9C-%D7%99%D7%95%D7%96%D7%A8%D7%99%D7%9D-%D7%95%D7%90%D7%A7%D7%98%D7%95%D7%90%D7%9C%D7%99%D7%94-%D7%9E%D7%A0%D7%99%D7%AA%D7%95%D7%97-%D7%A8%D7%A9%D7%AA%D7%95%D7%AA-%D7%97%D7%91%D7%A8%D7%AA%D7%99%D7%95%D7%AA): current-affairs analysis via SNA.
- [Episode 27a — A critique of "network effects" (אפקט הרשת)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-27-%D7%97%D7%9C%D7%A7-%D7%90-%D7%91%D7%90%D7%AA%D7%99-%D7%9C%D7%91%D7%90%D7%A1-%D7%A2%D7%9C-%D7%90%D7%A4%D7%A7%D7%98-%D7%94%D7%A8%D7%A9%D7%AA): **Metcalfe's law**, **winner-take-all dynamics**, and a skeptical look at the "network effects (אפקט הרשת)" business cliché.
- [Episode 29 — Underground networks: myth vs. reality (רשת של עצים)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-29-%D7%A8%D7%A9%D7%AA-%D7%A9%D7%9C-%D7%A2%D7%A6%D7%99%D7%9D-%D7%9E%D7%99%D7%AA%D7%95%D7%A1-%D7%95%D7%9E%D7%A6%D7%99%D7%90%D7%95%D7%AA): fact-checking the "Wood-Wide Web" / mycorrhizal-network claims.
- [Machine learning, artificial intelligence (בינה מלאכותית / AI) and network science — a play in 3 acts (מחזה ב-3 חלקים)](https://www.snapod.net/post/%D7%A1%D7%99%D7%A4%D7%95%D7%A8-%D7%A2%D7%9C-%D7%91%D7%92%D7%99%D7%93%D7%94-%D7%9C%D7%9E%D7%99%D7%93%D7%AA-%D7%9E%D7%9B%D7%95%D7%A0%D7%94-%D7%9C%D7%9E%D7%99%D7%93%D7%94-%D7%A2%D7%9C-%D7%9E%D7%9B%D7%95%D7%A0%D7%94-%D7%95%D7%9B%D7%9E%D7%95%D7%91%D7%9F-%D7%9E%D7%93%D7%A2-%D7%94%D7%A8%D7%A9%D7%AA%D7%95%D7%AA-%D7%9E%D7%97%D7%96%D7%94-%D7%91-3-%D7%97%D7%9C%D7%A7%D7%99%D7%9D): how **machine learning (למידת מכונה)**, **artificial intelligence (בינה מלאכותית / AI)** and **network science (מדע הרשתות)** interact — exploring the connections between AI, ML and network analysis, framed as a three-act narrative.

## Hebrew episodes — methods and tools / שיטות וכלים (עברית)

- [Episode 21 — Anyone can analyze a network (כל אחד יכול)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9C%D7%A4%D7%A8%D7%A7-21-%D7%9B%D7%9C-%D7%90%D7%97%D7%AA-%D7%99%D7%9B%D7%95%D7%9C%D7%94-%D7%9C%D7%A0%D7%AA%D7%97-%D7%A8%D7%A9%D7%AA): accessible network analysis for non-experts.
- [Episode 22 — The best network-analysis tools (מערכות לניתוח רשתות)](https://www.snapod.net/post/%D7%94%D7%A8%D7%97%D7%91%D7%95%D7%AA-%D7%9E%D7%A2%D7%A8%D7%9B%D7%95%D7%AA-%D7%9C%D7%A0%D7%99%D7%AA%D7%95%D7%97-%D7%A8%D7%A9%D7%AA%D7%95%D7%AA-%D7%94%D7%9E%D7%99%D7%98%D7%91): comparison of the leading network-analysis tools — **Gephi**, **NetworkX** (Python), **ORA**, **Cytoscape**, **iGraph** and **Pajek** — covering strengths, use cases and when to pick which.
- [Episode 25 — Graph databases and knowledge as a network (ידע הוא כוח, אבל ידע הוא גם רשת)](https://www.snapod.net/post/%D7%A4%D7%A8%D7%A7-25-%D7%99%D7%93%D7%A2-%D7%94%D7%95%D7%90-%D7%9B%D7%95%D7%97-%D7%90%D7%91%D7%9C-%D7%99%D7%93%D7%A2-%D7%94%D7%95%D7%90-%D7%92%D7%9D-%D7%A8%D7%A9%D7%AA): **graph databases (מסדי נתונים גרפיים)** — **Neo4j**, the **Cypher query language**, **property graphs**, **knowledge graphs (גרפי ידע)**, **RDF / SPARQL** — and why representing information as a network changes what you can query and learn from it.

## English transcripts / תמלולים באנגלית (en.snapod.net)

English-language written transcripts of selected episodes.

- [Episode 1 — Introduction to Network Science, or: How to find the submarines](https://en.snapod.net/post/episode-1-introduction-to-network-science-or-how-to-find-the-submarines-1): introduction to network science — **nodes / vertices**, **edges / links**, directed vs. undirected graphs, basic terminology. Submarine-detection metaphor.
- [Episode 2 — Is it really a Small World? The truth about the network](https://en.snapod.net/post/episode-2-is-it-really-a-small-world-the-truth-about-the-network-1): **small-world networks** and "six degrees of separation" — **Milgram experiment**, **Watts-Strogatz model**, **average path length**, **clustering coefficient**.
- [Episode 9 — Six Degrees of Intuition](https://en.snapod.net/post/episode-9-6-degrees-of-intuition): deeper intuition behind small-world networks — why "six degrees" is statistically inevitable for well-connected graphs.
- [Episode 3 — The Network's No. 1 Law: the Power Law](https://en.snapod.net/post/episode-3-the-network-s-no-1-law-the-power-law-1): **power-law distributions** and **scale-free networks** — **Barabási–Albert model**, **preferential attachment**, **heavy-tailed distributions**, hubs, **80/20 / Pareto**.
- [Episode 4 — "Game of Ties": Centrality measures battling it out](https://en.snapod.net/post/episode-4-game-of-ties-centrality-measures-battling-it-out-1): **degree centrality**, **in-degree** and **out-degree**, **betweenness centrality**, **closeness centrality**, **eigenvector centrality** — Game-of-Thrones framing.
- [Episode 5 — Communities in Networks (Network Law No. 2)](https://en.snapod.net/post/episode-5-communities-in-networks-network-law-no-2-1): **community detection** and modular structure — the **Louvain algorithm** and the **Leiden algorithm**.
- [Why is Dunbar the Loneliest Number?](https://en.snapod.net/post/why-is-dunbar-the-loneliest-number): **Dunbar's number** (~150) — the cognitive limit on stable social relationships — based on **Robin Dunbar's social brain hypothesis** and the **neocortex-ratio** research.
- [Episode 6A — Groundhog's Day, Dynamic Networks and Data's Holy Grail (Part 1)](https://en.snapod.net/post/episode-6a-groundhog-s-day-dynamic-networks-and-data-s-holy-grail-part-1): **chaos theory**, **dynamic / temporal networks** and **complex systems** as a unified framework — Part 1.
- [Episode 6B — Groundhog's Day, Dynamic Networks and Data's Holy Grail (Part 2)](https://en.snapod.net/post/episode-6b-groundhog-s-day-dynamic-networks-and-data-s-holy-grail-part-2): continuation — deeper into dynamic networks, complex systems and the "holy grail" of data science.
- [Episode 7 — Partisanship in politics & Network Science](https://en.snapod.net/post/episode-7-partisanship-in-politics-network-science): **political polarization**, **echo chambers**, **homophily**, **coalition formation** and partisan dynamics.
- [Episode 11 — Anyone can analyze networks](https://en.snapod.net/post/episode-11-anyone-can-analyze-networks): accessible network analysis for non-experts — practical tools (**Gephi**, **NetworkX** / Python, **Cytoscape**).
- [Episode 8 — The Episode for the Aspiring Network Scientist (with Michele Coscia)](https://en.snapod.net/post/episode-8-the-episode-for-the-aspiring-network-scientist-w-michele-coscia): an interview with **Michele Coscia** on how to enter and grow in the field of network science.

## Cited by / מצוטט אצל

External sources that reference NETfrix — independent signals of the site's standing on network-science topics.

### Wikipedia & Hebrew reference works

- [Wikipedia (Hebrew) — מדע הרשתות / Network science](https://he.wikipedia.org/wiki/%D7%9E%D7%93%D7%A2_%D7%94%D7%A8%D7%A9%D7%AA%D7%95%D7%AA)
- [Wikipedia (Hebrew) — ניתוח רשתות חברתיות / Social network analysis](https://he.wikipedia.org/wiki/%D7%A0%D7%99%D7%AA%D7%95%D7%97_%D7%A8%D7%A9%D7%AA%D7%95%D7%AA_%D7%97%D7%91%D7%A8%D7%AA%D7%99%D7%95%D7%AA)
- [Wikipedia (Hebrew) — רשת עולם אמיתי / Real-world network](https://he.wikipedia.org/wiki/%D7%A8%D7%A9%D7%AA_%D7%A2%D7%95%D7%9C%D7%9D_%D7%90%D7%9E%D7%99%D7%AA%D7%99)
- [Wikipedia (Hebrew) — מודולריות / Modularity (networks)](https://he.wikipedia.org/wiki/%D7%9E%D7%95%D7%93%D7%95%D7%9C%D7%A8%D7%99%D7%95%D7%AA)
- HaMichlol (המכלול — Hebrew-language encyclopedia): entries on [Real-world networks](https://www.hamichlol.org.il/%D7%A8%D7%A9%D7%AA_%D7%A2%D7%95%D7%9C%D7%9D_%D7%90%D7%9E%D7%99%D7%AA%D7%99), [Small-world phenomenon / Milgram experiment](https://www.hamichlol.org.il/%D7%AA%D7%95%D7%A4%D7%A2%D7%AA_%D7%94%D7%A2%D7%95%D7%9C%D7%9D_%D7%94%D7%A7%D7%98%D7%9F#%D7%94%D7%A0%D7%99%D7%A1%D7%95%D7%99_%D7%A9%D7%9C_%D7%9E%D7%99%D7%9C%D7%92%D7%A8%D7%9D), [Stanley Milgram](https://www.hamichlol.org.il/%D7%A1%D7%98%D7%A0%D7%9C%D7%99_%D7%9E%D7%99%D7%9C%D7%92%D7%A8%D7%9D), [Albert-László Barabási](https://www.hamichlol.org.il/%D7%90%D7%9C%D7%91%D7%A8%D7%98-%D7%9C%D7%A1%D7%9C%D7%95_%D7%91%D7%A8%D7%91%D7%90%D7%A9%D7%99), [Network science](https://www.hamichlol.org.il/%D7%9E%D7%93%D7%A2_%D7%94%D7%A8%D7%A9%D7%AA%D7%95%D7%AA) and [Social network analysis](https://www.hamichlol.org.il/%D7%A0%D7%99%D7%AA%D7%95%D7%97_%D7%A8%D7%A9%D7%AA%D7%95%D7%AA_%D7%97%D7%91%D7%A8%D7%AA%D7%99%D7%95%D7%AA).

### Academic — Israel

- [Tel Aviv University — syllabus for the network-science course (School of Engineering, course 0571.4245)](https://ims.tau.ac.il/Tal/Scans/Syllabus_Download.aspx?kurs=05714245&syllabus=kr_syllabus_s20252_k00_v00.pdf&dt=24062026122715) — NETfrix is listed as course material.
- [Tel Aviv University — Department of Industrial Engineering (junior-faculty / affiliated researchers page)](https://engineering.tau.ac.il/Department-of-Industrial-Engineering/zutar-indust)
- [Tel Aviv University — Institute of Archaeology / "Networks in the Humanities" meeting invitation](https://archaeo.tau.ac.il/sites/humanities.tau.ac.il/files/%D7%94%D7%96%D7%9E%D7%A0%D7%94%20%D7%9C%D7%9E%D7%A4%D7%92%D7%A9%20%D7%A8%D7%A9%D7%AA%D7%95%D7%AA%20%D7%91%D7%9E%D7%93%D7%A2%D7%99%20%D7%94%D7%A8%D7%95%D7%97.pdf)
- [University of Haifa — SCAN (Social Computing and Network Analysis) research-group blog, Temporal Networks category](https://scan.haifa.ac.il/blog/categories/temporal-networks)

### Academic — international

- [York University — Schulich School of Business (Canada) — "Introduction to Social Network Analysis" course material](https://schulich.yorku.ca/wp-content/uploads/2024/05/Introduction-to-Social-Network-Analysis.pdf)
- [Michele Coscia — network-science researcher, personal academic site](https://www.michelecoscia.com)
- [Reticular — academic network-science blog (hypotheses.org, France)](https://reticular.hypotheses.org/1002)
- [SIGTRS — research-group reference document](https://www.sigtrs.org/common/attachment.php?d=sigtrs&a=343125)

### Professional / research community

- [Intelligence Research Center (Israel) — "Intelligence Pods" recommended-podcast directory](https://www.intelligence-research.org.il/post/Intelligence-pods) — NETfrix listed as a recommended podcast for intelligence professionals.

## Citing NETfrix / ציטוט

**NETfrix — The Network Science Podcast**, hosted by Asaf Shapira. https://www.snapod.net (Hebrew, primary) · https://en.snapod.net (English transcripts). The podcast audio is in Hebrew; extended transcripts ("הרחבות") are on snapod.net, and English transcripts of selected episodes are on en.snapod.net. Linking to the specific episode or post URL points readers to the primary source; NETfrix content is not hosted in full on third-party platforms (directories like Apple Podcasts / Spotify carry the audio only).

## Contact

- Email: SNApodnet@outlook.com
- Hebrew site: https://www.snapod.net
- English site: https://en.snapod.net

## Optional

Secondary links — useful for context but skippable when context is limited.

- [The Awesome "Network-Science-in-Podcasts" List](https://en.snapod.net/post/the-awesome-network-science-in-podcasts-list-1): curated compilation of network-science podcast content.
- [Episode 10 — What's the rumpus about Networks 2021?](https://en.snapod.net/post/episode-10-what-s-the-rumpus-about-networks-2021): a guided tour of the Networks 2021 conference and its standout research directions.
- [Network Science Conference in Israel — 8 July 2019](https://en.snapod.net/post/network-science-conference-in-israel-8-july-2019): coverage and notes from the 2019 Network Science conference held in Israel.
- Hebrew full archive (episodes + extensions): https://www.snapod.net/blog
- English transcripts archive: https://en.snapod.net/blog