Social data: Biases, methodological pitfalls, and ethical boundaries

A Olteanu, C Castillo, F Diaz, E Kıcıman - Frontiers in big data, 2019 - frontiersin.org
Social data in digital form—including user-generated content, expressed or implicit relations
between people, and behavioral traces—are at the core of popular applications and …

Statistical challenges in online controlled experiments: A review of a/b testing methodology

N Larsen, J Stallrich, S Sengupta, A Deng… - The American …, 2024 - Taylor & Francis
The rise of internet-based services and products in the late 1990s brought about an
unprecedented opportunity for online businesses to engage in large scale data-driven …

Social simulacra: Creating populated prototypes for social computing systems

JS Park, L Popowski, C Cai, MR Morris… - Proceedings of the 35th …, 2022 - dl.acm.org
Social computing prototypes probe the social behaviors that may arise in an envisioned
system design. This prototy** practice is currently limited to recruiting small groups of …

A causal test of the strength of weak ties

K Rajkumar, G Saint-Jacques, I Bo**ov, E Brynjolfsson… - Science, 2022 - science.org
The authors analyzed data from multiple large-scale randomized experiments on LinkedIn's
People You May Know algorithm, which recommends new connections to LinkedIn …

[HTML][HTML] The effects of remote work on collaboration among information workers

L Yang, D Holtz, S Jaffe, S Suri, S Sinha… - Nature human …, 2022 - nature.com
Abstract The coronavirus disease 2019 (COVID-19) pandemic caused a rapid shift to full-
time remote work for many information workers. Viewing this shift as a natural experiment in …

[PDF][PDF] The impact of machine learning on economics

S Athey - The economics of artificial intelligence: An agenda, 2018 - nber.org
This paper provides an assessment of the early contributions of machine learning to
economics, as well as predictions about its future contributions. It begins by briefly …

[LIBRO][B] Trustworthy online controlled experiments: A practical guide to a/b testing

R Kohavi, D Tang, Y Xu - 2020 - books.google.com
Getting numbers is easy; getting numbers you can trust is hard. This practical guide by
experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate …

The econometrics of randomized experiments

S Athey, GW Imbens - Handbook of economic field experiments, 2017 - Elsevier
In this chapter, we present econometric and statistical methods for analyzing randomized
experiments. For basic experiments, we stress randomization-based inference as opposed …

Big data, data science, and analytics: The opportunity and challenge for IS research

R Agarwal, V Dhar - Information systems research, 2014 - pubsonline.informs.org
We address key questions related to the explosion of interest in the emerging fields of big
data, analytics, and data science. We discuss the novelty of the fields and whether the …

[PDF][PDF] Online controlled experiments and A/B tests

R Kohavi, R Longbotham - … of machine learning and data mining, 2015 - exp-platform.com
Many good resources are available with motivation and explanations about online
controlled experiments (Kohavi et al. 2009a, 2020; Thomke 2020; Luca and Bazerman …