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.

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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.

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Bad bots do good: Random artificial intelligence helps people coordinate

“To figure out whether random AI can help people coordinate, Hirokazu Shirado, a sociologist and systems engineer, and Nicholas Christakis, a sociologist and physician, both at Yale University, asked volunteers to play a simple online game. Each person controlled one node among 20 in a network. The nodes were colored green, orange, or purple, and people could change their node color at any time. The goal was for no two adjacent nodes to share the same color, but players could see only their color and the colors of the nodes to which they were connected, so sometimes settling conflicts with neighbors raised unseen conflicts between those neighbors and their neighbors. If the network achieved the goal before the 5-minute time limit was up, all players in the network received extra payment. The researchers recruited 4000 players and placed them in 230 randomly generated networks.
Some of the networks had 20 people controlling the nodes, but others had three of the most central or well-connected nodes already colored in such a way that they fit one of the solutions. (Each network had multiple solutions.) And some of the networks had 17 people and three bots, or simple AI programs, in charge of the nodes. In some networks, the bot-controlled nodes were placed centrally, in some they were placed peripherally, and in some they were placed randomly. The bots also varied in how much noise, or randomness, influenced their choice of node color. In some networks, every 1.5 seconds the bots picked whatever color differed from the greatest number of neighbors—generally a good strategy among people playing the game. In some networks, they followed this strategy, but 10% of the time they would pick randomly. And in some networks, they would pick randomly 30% of the time.
All of the networks with bots performed the same as the networks with 20 people, except for one type. The networks in which the bots were placed centrally and randomized their decisions 10% of the time outperformed the all-human networks. They solved the coordination game within the time limit more frequently (85% versus 67% of the time). And the median time spent on the task was 103 seconds versus 232 seconds, a significant difference, the researchers report today in Nature. The fact that bots with 0% noise or 30% noise did not outperform humans means that there’s a Goldilocks zone of randomness.
What’s more, the bot-aided networks performed just as well as the networks that already had a head start—those with three nodes preset to fit a solution. But whereas the set-color networks required top-down control, the noisy bots achieved equal results with just a bit of local randomness. “We get the same bang,” Christakis says. “To me that was a beautiful result.””
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Noshir Contractor participates on a panel at the Digital Innovation Networks Forum

On June 27th Noshir Contractor will take part in a one-day Digital Innovation Networks Forum organized by FIRE – Future Internet Research & Experimentation initiative in Brussels, Belgium. He will be participating in a panel titled “How does the process of innovation need to change as a consequence of increased digitisation and connectivity?” This is a live panel debate bringing together experts from around the world (US, Europe), moderated by Michael Boniface (IT Innovation, FIRE Study). Noshir will present on “The impact of technology affordances on engendering innovation in multidimensional knowledge networks at scale.”
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Marlon Twyman presents two posters at NetSci 2017

SONIC graduate student, Marlon Twyman, presented two posters at the International School and Conference on Network Science (NetSci) 2017 held in Indianapolis, Indiana on June 19-23, 2017. One poster explores the integration of shared cognition, dynamic task networks, and agent-based modeling when studying collaboration within astronaut teams. The other poster investigates the performance of organizations when using various search strategies to find members of problem-solving teams.

Poster Citations:

Marlon Twyman, Leslie DeChurch, & Noshir Contractor. Using a Network Approach for Modeling Shared Cognition of Astronaut Teams. NetSci 2017 International School and Conference on Network Science, Indianapolis, Indiana, June 19-23, 2017. Twyman, M., Ma, L., Srivatsa, M., Cansever, D., & Contractor, N. Searching Networks to Assemble Teams. NetSci 2017 International School and Conference on Network Science, Indianapolis, Indiana, June 19-23, 2017.

Marlon Twyman,  Liang Ma, Mudhakar Srivatsa, Derya Cansever, & Noshir Contractor. Searching Networks to Assemble Teams. NetSci 2017 International School and Conference on Network Science, Indianapolis, Indiana, June 19-23, 2017.

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Diego Gomez-Zara presented two posters at NetSci 2017

On June 23rd, SONIC’s Ph.D. student Diego Gómez-Zará is going to present his research on social movements at the International School and Conference on Network Science (NetSci). This year, the conference will be hosted in Indianapolis, USA. Diego will present two posters “The role of social movement organizations and their leaders in Twitter: Evidence from the Chilean Student Movement” and “Using Relational Event Modeling to explain movements’ emergence in Twitter: Evidence from the Chilean Student Movement.”

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New NASA Grant – Project FUSION

We are very excited to receive a new grant from NASA, on which SONIC’s Noshir Contractor is a Co-Investigator.

Project FUSION: Facilitating Unified Systems of Interdependent Organizational Networks

Project FUSION was among seven proposals, selected by NASA’s Human Research Program to help answer questions about astronaut health and performance during future long-duration missions beyond low-Earth orbit. These proposals will investigate the impact of the space environment on various aspects of astronaut health, including behavioral health and performance, cardiovascular alterations, human factors and radiation effects. All of the selected projects will contribute to NASA’s long-term plans for deep space exploration, including to Mars.

Project Team: Dorothy Carter, University of Georgia (PI), Marissa Shuffler, Clemson University (Co-I), Leslie DeChurch, Northwestern (Co-I), Noshir Contractor, Northwestern (Co-I), Aaron Schecter, University of Georgia  (Co-I), Shawn Burke, University of Central Florida (Consultant), Stephen Zaccaro, George Mason University (Consultant), & Lauren Landon, Wyle Laboratories, Inc. (Consultant)

Sending a team of humans to Mars will require extreme forms of teamwork across complex “Multiteam Systems” comprised of multiple teams that are separated by unprecedented degrees of space and time (e.g., mission control teams, spaceflight crews). In “Project FUSION: Facilitating Unified Systems of Interdependent Organizational Networks” we will combine findings from qualitative research with NASA personnel, agent-based computational models, and laboratory studies at The University of Georgia, Northwestern University, and NASA analog environments to uncover the drivers of crucial psycho-social teamwork relationships, such as trust, influence, and shared understanding, within and across teams in Spaceflight Multiteam Systems. Based on this program of research, we will develop and deliver countermeasures, including training and debriefing protocols, to help NASA prepare for and monitor multiteam collaboration throughout long-duration space exploration missions.

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Noshir Contractor was a plenary speaker at the Collective Intelligence Conference

Noshir Contractor gave a plenary talk in a session titled “Organizing and Organizations” at the Collective Intelligence Conference. CI is the fifth annual interdisciplinary conference dedicated to advancing our understanding of collective intelligence and the workings of groups. The conference took place at New York University’s Tandon School of Engineering in Brooklyn, NY, on June 15-16, 2017.

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