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Jake M. Hofman
Microsoft
43Publications
22H-index
4,292Citations
Publications 39
Newest
#1Jake M. HofmanH-Index: 22
#2Daniel G. GoldsteinH-Index: 32
view all 3 authors...
#1Amit SharmaH-Index: 14
#2Jake M. HofmanH-Index: 22
Last.Duncan J. WattsH-Index: 51
view all 3 authors...
2 CitationsSource
#1Duncan J. WattsH-Index: 51
Last.Matthew J. SalganikH-Index: 17
view all 9 authors...
Apr 21, 2018 in CHI (Human Factors in Computing Systems)
#1Christopher Riederer (Columbia University)H-Index: 7
#2Jake M. Hofman (Microsoft)H-Index: 22
Last.Daniel G. Goldstein (Microsoft)H-Index: 32
view all 3 authors...
Laypeople are frequently exposed to unfamiliar numbers published by journalists, social media users, and algorithms. These figures can be difficult for readers to comprehend, especially when they are extreme in magnitude or contain unfamiliar units. Prior work has shown that adding "perspective sentences" that employ ratios, ranks, and unit changes to such measurements can improve people's ability to understand unfamiliar numbers (e.g., "695,000 square kilometers is about the size of Texas"). Ho...
1 CitationsSource
Despite a growing body of research focused on creating interpretable machine learning methods, there have been few empirical studies verifying whether interpretable methods achieve their intended effects on end users. We present a framework for assessing the effects of model interpretability on users via pre-registered experiments in which participants are shown functionally identical models that vary in factors thought to influence interpretability. Using this framework, we ran a sequence of la...
43 Citations
#1Omar Alonso (Microsoft)H-Index: 19
#2Vasileios Kandylas (Microsoft)H-Index: 3
Last.Siddhartha Sen (Microsoft)H-Index: 13
view all 5 authors...
Every day millions of users share links and post comments on different social networks. At scale, this behavior can be very useful for building a new type of search engine that exploits relevant links and their associated metadata in a temporal fashion. Our goal is to find links that are relevant on social networks as a mechanism to discover what people are talking about at a given point in time and make such information searchable and persistent. In other words, a continually updated archive of...
3 CitationsSource
#1Jake M. Hofman (Microsoft)H-Index: 22
#2Amit Sharma (Microsoft)H-Index: 14
Last.Duncan J. Watts (Microsoft)H-Index: 51
view all 3 authors...
Historically, social scientists have sought out explanations of human and social phenomena that provide interpretable causal mechanisms, while often ignoring their predictive accuracy. We argue that the increasingly computational nature of social science is beginning to reverse this traditional bias against prediction; however, it has also highlighted three important issues that require resolution. First, current practices for evaluating predictions must be better standardized. Second, theoretic...
73 CitationsSource
May 7, 2016 in CHI (Human Factors in Computing Systems)
#1Pablo Barrio (Columbia University)H-Index: 4
#2Daniel G. Goldstein (Microsoft)H-Index: 32
Last.Jake M. Hofman (Microsoft)H-Index: 22
view all 3 authors...
How many guns are there in the USA? What is the incidence of breast cancer? Is a billion dollar budget cut large or small? Advocates of scientific and civic literacy are concerned with improving how people estimate and comprehend risks, measurements, and frequencies, but relatively little progress has been made in this direction. In this article we describe and test a framework to help people comprehend numerical measurements in everyday settings through simple sentences, termed perspectives, th...
7 CitationsSource
Apr 11, 2016 in WWW (The Web Conference)
#1Travis Martin (UM: University of Michigan)H-Index: 9
#2Jake M. Hofman (Microsoft)H-Index: 22
Last.Duncan J. Watts (Microsoft)H-Index: 51
view all 5 authors...
How predictable is success in complex social systems? In spite of a recent profusion of prediction studies that exploit online social and information network data, this question remains unanswered, in part because it has not been adequately specified. In this paper we attempt to clarify the question by presenting a simple stylized model of success that attributes prediction error to one of two generic sources: insufficiency of available data and/or models on the one hand; and inherent unpredicta...
35 CitationsSource
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