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June 8, 2020 Shankar Iyer, Justin Cheng, Nick Brown, Xiuhua Wang
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When Does Trust in Online Social Groups Grow?

To better test the potential causal pathways between trust and behaviors or group properties, we paired a two-wave longitudinal survey of 2358 participants in Facebook Groups with logged activity on Facebook. Using latent change score modeling, we examined how trust may predict changes in behavior or group properties and how behaviors and group properties may predict changes in trust.
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April 25, 2020 Moira Burke, Justin Cheng, Bethany de Gant
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Social Comparison and Facebook: Feedback, Positivity, and Opportunities for Comparison

People compare themselves to one another both offline and online. The specific online activities that worsen social comparison are partly understood, though much existing research relies on people recalling their own online activities post hoc and is situated in only a few countries. To better understand social comparison worldwide and the range of associated behaviors on social media, a survey of 38,000 people from 18 countries was paired with logged activity on Facebook for the prior month.
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April 25, 2020 Sindhu Kiranmai Ernala, Moira Burke, Alex Leavitt, Nicole Ellison
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How Well Do People Report Time Spent on Facebook? An Evaluation of Established Survey Questions with Recommendations

This paper compares data from ten self-reported Facebook use survey measures deployed in 15 countries (N = 49,934) against data from Facebook’s server logs to describe factors associated with error in commonly used survey items from the literature.
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April 20, 2020 Jonathan Chang, Justin Cheng, Cristian Danescu-Niculescu-Mizil
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Don’t Let Me Be Misunderstood: Comparing Intentions and Perceptions in Online Discussions

Discourse involves two perspectives: a person’s intention in making an utterance and others’ perception of that utterance. The misalignment between these perspectives can lead to undesirable outcomes, such as misunderstandings, low productivity and even overt strife. In this work, we present a computational framework for exploring and comparing both perspectives in online public discussions.
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April 20, 2020 Jack Marriott, Birce Tezel, Zhang Liu, Nicolas Stier
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Trajectory Optimization of Solar-Powered High-Altitude Long Endurance Aircraft

Solar-powered high-altitude long endurance aircraft that harvest and store solar energy can fly indefinitely if they are able to close a 24-hour energy cycle. Perpetual endurance is possible when energy consumption does not exceed energy storage.
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December 2, 2019 Sam Daulton, Shaun Singh, Vashist Avadhanula, Drew Dimmery, Eytan Bakshy
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Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints

In this paper, we propose a novel Thompson sampling algorithm for multi-outcome contextual bandit problems with auxiliary constraints. We empirically evaluate our algorithm on a synthetic problem. Lastly, we apply our method to a real world video transcoding problem and provide a practical way for navigating the trade-off between safety and performance using Bayesian optimization.
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July 1, 2019 Dmitrii Avdiukhin, Sergey Pupyrev, Grigory Yaroslavtsev
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Multi-Dimensional Balanced Graph Partitioning via Projected Gradient Descent

Motivated by performance optimization of large-scale graph processing systems that distribute the graph across multiple machines, we consider the balanced graph partitioning problem. Compared to most of the previous work, we study the multi-dimensional variant in which balance according to multiple weight functions is required.
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June 26, 2019 Vincent Conitzer, Christian Kroer, Debmalya Panigrahi, Okke Schrijvers, Eric Sodomka, Nicolas Stier, Chris Wilkens
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Pacing Equilibrium in First-Price Auction Markets

In the isolated auction of a single item, second price is often preferable to first price in properties of theoretical interest. Unfortunately, single items are rarely sold in true isolation, so considering the broader context is critical when adopting a pricing strategy. In this paper, we show that this context is important in a model centrally relevant to Internet advertising: when items (ad impressions) are individually auctioned within the context of a larger system that is managing budgets, theory offers surprising support for using a first price auction to sell each individual item.
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June 24, 2019 Shankar Iyer, Lada Adamic
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When can overambitious seeding cost you?

Here, we extend earlier work by showing that the costs of overambitious seeding also appear in more traditional threshold models of collective behavior, once the possibility of permanent abandonment of the product is introduced. We further demonstrate that these costs can be mitigated by using conservative seeding approaches besides those that we explored in the earlier paper. Synthesizing these results with other recent work in this area, we identify general principles for when overambitious seeding can be of concern in the deployment of social products.
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June 1, 2019 Somit Gupta, Ronny Kohavi, Diane Tang, Ya Xu, Reid Andersen, Eytan Bakshy, Niall Cardin, Sumitha Chandran, Nanyu Chen, Dominic Coey, Mike Curtis, Alex Deng, Weitao Duan, Peter Forbes, Brian Frasca, Tommy Guy, Guido W. Imbens, Guillaume Saint Jacques, Pranav Kantawala, Ilya Katsev, Moshe Katzwer, Mikael Konutgan, Elena Kunakova, Minyong Lee, MJ Lee, Joseph Liu, James McQueen, Amir Najmi, Brent Smith, Vivek Trehan, Lukas Vermeer, Toby Walker, Jeffrey Wong, Igor Yashkov
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Top Challenges from the first Practical Online Controlled Experiments Summit

To understand the top practical challenges in running OCEs at scale, representatives with experience in large-scale experimentation from thirteen different organizations (Airbnb, Amazon, Booking.com, Facebook, Google, LinkedIn, Lyft, Microsoft, Netflix, Twitter, Uber, Yandex, and Stanford University) were invited to the first Practical Online Controlled Experiments Summit. All thirteen organizations sent representatives.
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