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Dear Reader,

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Welcome to the lucky Friday the 13th issue of the Data Science Briefing!

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This week’s newsletter spotlights the rapid evolution—and occasional pitfalls—of AI-driven content and tooling. Anthropic’s ambitious “Claude Explains” blog, which showcased AI-generated technical posts edited by humans, was abruptly shuttered after just a month, following criticism over unclear authorship and concerns about the reliability of AI-generated information. The short-lived project highlights ongoing tensions around transparency and trust in AI-assisted publishing. Meanwhile, in the developer trenches, firsthand accounts like “Field Notes From Shipping Real Code With Claude” and “A Thousand Tiny Optimisations” offer practical insights into deploying AI tools and refining codebases at scale. On the agent front, the debate continues: while some engineers share productive workflows for programming with AI agents, others argue that current agent models fall short as collaborative coding partners, underscoring the nuanced realities of integrating AI into daily development. Finally, the introduction of Magistral by Mistral AI signals growing competition in the reasoning model space, promising new benchmarks for advanced problem-solving capabilities.

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Recent research continues to blur the boundaries between computational modeling, language, and human behavior. The “LLM World of Words” project demonstrates how large language models can generate English free association norms, offering new insights into the structure of human-like semantic networks. Meanwhile, epidemic modeling has taken a behavioral turn, with comparative studies revealing that both data-driven and analytical feedback models are crucial for accurately forecasting pandemic dynamics. Notably, no single approach consistently outperforms others; instead, the integration of real-time behavioral data, such as mobility patterns, and theoretical feedback mechanisms provides the most robust predictions, especially during the volatile early stages of an outbreak. These advances underscore the growing importance of datasets and modeling techniques that capture the dynamic interplay between human cognition, decision-making, and large-scale social phenomena.

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This week's book is "Behavioral Network Science: Language, Mind, and Society" by T. T. Hills. You can find all the previous book recommendations on our website. In this week's video, we have a tutorial on Scraping Data from a Real Website.

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Data shows that the best way for a newsletter to grow is by word of mouth, so if you think one of your friends or colleagues would enjoy this newsletter, go ahead and forward this email to them. This will help us spread the word!

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Semper discentes,

The D4S Team

"Behavioral Network Science: Language, Mind, and Society" by T. T. Hills successfully bridges two distinct scientific domains, demonstrating how network analysis can reveal hidden patterns in human behavior. The book tackles an impressive scope of topics, from language evolution and childhood learning to cognitive aging, creativity, and social dynamics, while maintaining remarkable coherence throughout. What sets this work apart is Hills' commitment to practical application, equipping readers with concrete tools including an introductory guide to network science and accompanying R code that enables hands-on analysis.

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This practical approach makes the book uniquely valuable to a diverse audience. Behavioral scientists unfamiliar with network methods will find an accessible entry point, while data scientists can discover rich applications in behavioral research. Hills demonstrates particular skill in addressing contemporary social issues through a network lens, offering fresh perspectives on polarization, echo chambers, and conspiracy theories. The interdisciplinary framework proves especially powerful when examining how individual cognitive processes scale up to shape collective behavior and social structures.

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The book's most significant achievement lies in its clarity without oversimplification. Hills effectively conveys complex concepts with precision while maintaining an engaging and accessible tone. This balance makes "Behavioral Network Science" essential reading for anyone seeking to understand how network structures influence human behavior across scales—from individual minds to entire societies.

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1. ​Anthropic’s AI-generated blog dies an early death​ [techcrunch.com]
2. ​Field Notes From Shipping Real Code With Claude​ [diwank.space]
3. ​A Thousand Tiny Optimisations​ [leejo.github.io]
4. ​Why agents are bad pair programmers [justin.searls.co]
5. ​Magistral — the first reasoning model by Mistral AI [mistral.ai]
6. ​The Gentle Singularity [blog.samaltman.com]
7. ​How I program with Agents​ [https://crawshaw.io]

• ​The “LLM World of Words” English free association norms generated by large language models​ (K. Abramski, R. Improta, G. Rossetti, M. Stella)
• ​Comparative evaluation of behavioral epidemic models using COVID-19 data​ (N. Gozzi, N. Perra, A. Vespignani)
• ​Milgram’s experiment in the knowledge space: individual navigation strategies​ (M. Zhu, J. Kertész)
• ​Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability​ (M. Cargnelutti, C. Brobston, J. Hess, J. Cushman, K. Mukk, A. Scourtas, K. Courtney, G. Leppert, A. Watson, M. Whitehead, J. Zittrain)
• ​Reasoning Language Models: A Blueprint​ (M. Besta, J. Barth, E. Schreiber, A. Kubicek, A. Catarino, R. Gerstenberger, P. Nyczyk, P. Iff, Y. Li, S. Houliston, T. Sternal, M. Copik, G. Kwaśniewski, J. Müller, Ł. Flis, H. Eberhard, Z. Chen, H. Niewiadomski, T. Hoefler)
• ​OpenThoughts: Data Recipes for Reasoning Models​ (E. Guha, R. Marten, S. Keh, N. Raoof, G. Smyrnis, H. Bansal, M. Nezhurina, J. Mercat, T. Vu, Z. Sprague, A. Suvarna, B. Feuer, L. Chen, Z. Khan, E. Frankel, S. Grover, C. Choi, N. Muennighoff, S. Su, W. Zhao, J. Yang, S. Pimpalgaonkar, K. Sharma et al)
• ​Modern Minimal Perfect Hashing: A Survey​ (H.-P. Lehmann, T. Mueller, R. Pagh, G. E. Pibiri, P. Sanders, S. Vigna, S. Walzer)

Scraping Data from a Real Website

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All the videos of the week are now available in our YouTube playlist.

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