A manifesto for reproducible science

Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproducibility, evaluation and incentives. There is some evidence from both simulations and empirical studies supporting the likely effectiveness of these measures, but their broad adoption by researchers, institutions, funders and journals will require iterative evaluation and improvement. We discuss the goals of these measures, and how they can be implemented, in the hope that this will facilitate action toward improving the transparency, reproducibility and efficiency of scientific research.

Link: https://www.nature.com/articles/s41562-016-0021

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Evidence of complex contagion of information in social media: An experiment using Twitter bots

It has recently become possible to study the dynamics of information diffusion in techno-social systems at scale, due to the emergence of online platforms, such as Twitter, with millions of users. One question that systematically recurs is whether information spreads according to simple or complex dynamics: does each exposure to a piece of information have an independent probability of a user adopting it (simple contagion), or does this probability depend instead on the number of sources of exposure, increasing above some threshold (complex contagion)? Most studies to date are observational and, therefore, unable to disentangle the effects of confounding factors such as social reinforcement, homophily, limited attention, or network community structure. Here we describe a novel controlled experiment that we performed on Twitter using ‘social bots’ deployed to carry out coordinated attempts at spreading information. We propose two Bayesian statistical models describing simple and complex contagion dynamics, and test the competing hypotheses. We provide experimental evidence that the complex contagion model describes the observed information diffusion behavior more accurately than simple contagion. Future applications of our results include more effective defenses against malicious propaganda campaigns on social media, improved marketing and advertisement strategies, and design of effective network intervention techniques.

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Diego Gomez-Zara presenting at Computation+Journalism 2017

SONIC graduate student, Diego Gomez-Zara, will present one poster at the Computational + Journalism Symposium (C+J) 2017 held at Northwestern University on October 13th, 2017. We present a system that identifies the main entities of the article, and it uses dictionaries based on fictional characters and sentiment analysis to determine when an entity is being cast as a hero, villain, or a victim. This system interacts with news consumers directly through a browser extension. Our hope is that by informing readers when an entity is cast in one of these roles, we can make implicit bias explicit, and assist readers in applying their media literacy skills.

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Why Everyone Should See Themselves as a Leader

Sue Ashford, a professor at the University of Michigan’s Ross School of Business, breaks down her decades of research on leadership—who achieves it, and how a group grants it. She explains that the world isn’t divided into leaders and followers. Instead, it’s a state that everyone can reach, whether they’re officially in charge or not. She also explains why shared leadership benefits a team and organization. Ashford offers tips on how to effectively grow leadership in yourself and your employees.

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The ‘time machine’ reconstructing ancient Venice’s social networks

Machine-learning project will analyse 1,000 years of maps and manuscripts from the floating city’s golden age.

History hangs heavy at the Frari, and computer scientist Frédéric Kaplan likes it that way. He has an ambition to capture well over 1,000 years of records in dynamic digital form, encompassing the glorious era of the Most Serene Republic of Venice. The project, which he calls the Venice Time Machine, will scan documents including maps, monographs, manuscripts and sheet music. It promises not only to open up reams of hidden history to scholars, but also to enable the researchers to search and cross-reference the information, thanks to advances in machine-learning technologies.

Read the full article here.

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How to judge a book by its network

Taking advantage of the ‘customers who bought this item also bought’ feature of online commerce, this study constructed a co-purchase network of political books and science books. Researches found a clear division, which they label “partisan differences in the consumption of science”.

Both groups bought science books — more than 400,000 between them. But it was relatively unusual to find books that appealed to both liberals and conservatives. Members of each group — and their good friends — had different ideas about what made a good book. Buyers of “blue books” (the liberals) tended to pick from basic science topics, including physics, astronomy and zoology. “Red” customers preferred books that discussed applied and commercial science, such as medicine, criminology and geophysics. And whereas liberal choices tended to reflect mainstream thinking, “red books” tended to be co-purchased with a narrower subset of science books on the fringes of each subject.

Read the full article here.

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