Methodology Lineage
The research our stack is built on.
The nine-signal measurement stack draws from three disciplines with decades of peer-reviewed work behind them. These are starting points — not the complete reading list. If you want a fuller bibliography for a specific signal, capability, or claim, ask and we'll send it.
Neuromarketing & Consumer Neuroscience
The body of work establishing that neural and physiological measurement can predict consumer behavior — and the boundary conditions on that prediction.
Plassmann, H., Venkatraman, V., Huettel, S., & Yoon, C. (2015). Consumer Neuroscience: Applications, Challenges, and Possible Solutions. Journal of Marketing Research, 52(4), 427–435. link
Ramsøy, T. Z. (2015). Introduction to Neuromarketing & Consumer Neuroscience. Neurons Inc Press.
Smidts, A., Hsu, M., Sanfey, A. G., et al. (2014). Advancing consumer neuroscience. Marketing Letters, 25(3), 257–267. link
Affective Computing
The field that treats emotion as a computational signal — and is appropriately skeptical of one-to-one mappings between facial movement and felt emotion.
Picard, R. W. (1997). Affective Computing. MIT Press.
Calvo, R. A., & D'Mello, S. (2010). Affect detection: An interdisciplinary review of models, methods, and their applications. IEEE Transactions on Affective Computing, 1(1), 18–37. link
Barrett, L. F., Adolphs, R., Marsella, S., Martinez, A. M., & Pollak, S. D. (2019). Emotional Expressions Reconsidered: Challenges to Inferring Emotion From Human Facial Movements. Psychological Science in the Public Interest, 20(1), 1–68. link
Computational Social Science
The framework for studying behavior at population scale using digital traces — with explicit methodological guardrails for what those traces can and cannot say.
Lazer, D., Pentland, A., Adamic, L., et al. (2009). Computational Social Science. Science, 323(5915), 721–723. link
Pentland, A. (2014). Social Physics: How Good Ideas Spread—The Lessons from a New Science. Penguin Press.
Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. link
Lazer, D., Pentland, A., Watts, D. J., et al. (2020). Computational social science: Obstacles and opportunities. Science, 369(6507), 1060–1062. link
Want the specific citation behind a specific claim?
Any number, mechanism, or methodology choice we describe on this site is anchored in published work. Ask for the source — we'll send it, with the relevant passage flagged.