Martin Vargic has a new map of the internet (available here)

Automatic detection of influential actors in disinformation networks

• The weaponization of digital communications and social media to conduct disinformation campaigns at immense scale, speed, and reach presents new challenges to identify and counter hostile influence operations (IOs). This paper presents an end-to-end framework to automate detection of disinformation narratives, networks, and influential actors. The framework integrates natural language processing, machine learning, graph analytics, and a network causal inference approach to quantify the impact of individual actors in spreading IO narratives. We demonstrate its capability on real-world hostile IO campaigns with Twitter datasets collected during the 2017 French presidential elections and known IO accounts disclosed by Twitter over a broad range of IO campaigns (May 2007 to February 2020), over 50,000 accounts, 17 countries, and different account types including both trolls and bots. Our system detects IO accounts with 96% precision, 79% recall, and 96% area-under-the precision-recall (P-R) curve; maps out salient network communities; and discovers high-impact accounts that escape the lens of traditional impact statistics based on activity counts and network centrality. Results are corroborated with independent sources of known IO accounts from US Congressional reports, investigative journalism, and IO datasets provided by Twitter.

The geometry of decision-making

• Choosing among spatially-distributed options is a central challenge for animals, from deciding among alternative potential food sources or refuges, to choosing with whom to associate. Using an integrated theoretical and experimental approach (employing immersive virtual reality), we consider the interplay between movement and vectorial integration during decision-making regarding two, or more, options in space. In computational models of this process we reveal the occurrence of spontaneous and abrupt “critical” transitions (associated with specific geometrical relationships) whereby organisms spontaneously switch from averaging vectorial information among, to suddenly excluding one, among the remaining options. This bifurcation process repeats until only one option—the one ultimately selected—remains. Thus we predict that the brain repeatedly breaks multi-choice decisions into a series of binary decisions in space-time. Experiments with fruit flies, desert locusts, and larval zebrafish reveal that they exhibit these same bifurcations, demonstrating that across taxa and ecological context, we show that there exist fundamental geometric principles that are essential to explain how, and why, animals move the way they do.

Book

• Working on map chapter/article
• 2:00 Meeting with Michelle

SBIR

• Pulled some papers for Ron
• Need to sync up with Rukan – done! Really nice work. We need to produce better statistics for analyzing ensembles
• More writing. The abstracts are due Monday! Uploaded map:

GPT Agents

• Finished processing the Yelp files. Backing up the DB
• 3:00 meeting?
• Training corpora
  • Only star ratings
  • Business name, type, review, then star ratings
• Generate 1,000,000 line samples that are based on different business?
• Automatic ablation study of 10k, 20k, … 1M corpora
• Look for different ways to name the same thing that tells something about who you are. (look for racist ways of describing food?) Analog of #chinavirus and #Sars-Cov-2
  • Paki vs. Pakistani, Curry vs. Indian, Chinese vs. Takeout.
  • Invite all for a presentation next Tuesday at 3:00 for 90 minutes (include Fatima and Arpita)