Roberta Sinatra was one of the 19 recipients of this year’s Villum Young Investigators grant!
The Villum Young Investigator programme (YIP) focuses on attracting and retaining talented young Danish and international researchers at Danish universities. The aim is to support the development of high-level international research environments in the universities.
Roberta’s winning proposal was awarded with DKK 6M:
Bias Explained: Pushing Algorithmic Fairness with Models and Experiments
Algorithms for ranking scientific information have an issue: they use citations, which are ingrained with human biases. Therefore, their output is also biased, creating inequalities and raising concerns of discrimination. This project aims to uncover the mathematical bias mechanisms that drive different citation trajectories given same quality, and to use them for creating fair algorithms.
We are overwhelmed with joy for Roberta’s success, and are looking forward to her future groundbreaking research. The grant will allow the recruitment of one PhD student and two postdocs – so stay tuned for upcoming job calls.
In the past two years, NERDS member Michele Coscia has been working on a textbook for the Network Analysis class he teaches at ITU. This “Atlas for the Aspiring Network Scientist”, has now reached version 1.0, and 760 pages, and is available for anyone to read for free: https://arxiv.org/abs/2101.00863
The Atlas aims at being broad, not deep, to be a pointer to the things you need to know about Network Science rather than a deep explanation of those things.
Consider this a v1.0 of a continuous effort. There are many things to improve: language, concepts, references, figures. Please contact Michele with any comments.
Michele also plans to have interactive figures on the website in the future. Version 1.0 was all financed using his research money and time. For the future, Michele will need some support to do this in his free time. If you feel like encouraging this effort, you can consider becoming a member on Patreon.
Find a more detailed explanation of The Atlas for the Aspiring Network Scientist on Michele’s page: https://www.michelecoscia.com/?p=1913
Click for a video demo of MNET-VR
Multilayer networks are an increasingly popular way to model complex relations between various types of entities and they have been applied to a large number of real-world data sets. Their intrinsic complexity makes the visualization of this type of network extremely challenging and still an open research area. To help the visual exploration of complex multilayer network structures, today we are releasing MNET-VR. MNET-VR is the output of a research project carried on with Leonard Maxim and supported by the Digital Design Department. MNET-VR explores the potential of Virtual Reality to visualize this type of network structure.
MNET-VR offers basic functions to visualize and filter multilayer network structures. MNET-VR does not offer, at this stage, the possibility to manipulate the network layout. A proper 3D layout of the network can be obtained through the R package multinet. While its primary goal is to explore multilayer networks, MNET-VR can also be used to visualize single layer networks using igraph and multinet. The export of of the files for visualization is done through two simple R functions that we make available on the website. MNET-VR is designed for Oculus Rift/Oculus Quest with Link.
We have published two new papers in December:
- The Node Vector Distance Problem in Complex Networks, by M. Coscia, A. Gomez-Lievano, F. Neffke, published in ACM Computing Surveys
The paper develops a new measure to quantify the distances between sets of nodes, with important applications on network dynamics such as spread of diseases.
Read Michele’s blog post about it: https://www.michelecoscia.com/?p=1898
- Data-driven strategies for optimal bicycle network growth, by L.G. Natera Orozco, F. Battiston, G. Iniguez, M. Szell, published in Royal Society Open Science
Here we investigate the network structure of bicycle networks in cities around the world, and find that they consist of hundreds of disconnected patches, even in cycling-friendly cities like Copenhagen. To connect these patches, we develop and apply data-driven, algorithmic network growth strategies, showing that small but focused investments allow to significantly increase the connectedness and directness of urban bicycle networks.
Today Roberta Sinatra received this year’s Complex Systems Society Junior Scientific Award!
The award was given for Roberta’s
pioneer contributions to the science of science and success, having had an impact in multiple fields, from network science to computational social science and scientometrics
The award is given once a year to two young CSS researchers, aimed at recognizing extraordinary scientific achievements: https://cssociety.org/community/css-awards
Tomorrow, Friday Oct 30, 12:15-13:15, Maksim Kitsak from Delft University of Technology will give a talk via zoom. Please contact Tiago Cunha (firstname.lastname@example.org) if you wish to join:
Invited talk Maksim Kitsak
Three NERDS were promoted from Assistant Professor to Associate Professor as of today, Oct 1: Michele Coscia, Roberta Sinatra, Michael Szell
That’s all 🙂
Over the summer our research group, and many others at ITU, moved to a new office space, taking over a building from DR, the national Danish Broadcasting Corporation. We NERDS secured a fancy new room housing all our members, which we have started to utilize and develop after the lockdown.
Our room and new address is:
3F11, Kaj Munks Vej 9, DR P4 building (a.k.a. Emil Holms Kanal)
After entering the building, take the elevators on the right. On the 3rd floor go left to the end of the hallway. See you!
We are inviting contributions to the “Complex Networks and Economics” issue of the Frontiers in Big Data journal, co-edited by NERDS Michele Coscia and the NERDS-friendly and really excellent Morgan Frank
, recently appointed assistant professor at the University of Pittsburgh.
Some additional information about what we’re looking for:
We think it is important to lift people out of poverty and to guarantee them decent standards of living. However, to successfully promote economic growth, the high degree of complexity of the global market and regional industrial activities requires an integrated understanding of the ecosystem of complementary actors, knowhow, and capital. The way to do so is by conceptualizing productivity as an emerging property of a complex system made by simpler interacting parts. Complex systems are notoriously difficult to control but quantifying these interactions can identify the bottlenecks to growth and inform policy to bolster economic convergence. Using tools from economics, complex systems, and network science, we seek crucial insights that enable economic convergence.
The goal of this Research Topic is to collect contributions using complex network analysis to model economic systems and to gain insights into economic development which has proven to be a valuable scientific undertaking. We want to explore the potential applications of complex network analysis to foster our understanding of complex economic systems. We welcome contributions in the broad areas of:
• Mapping the relationship of complex economic activities to build Product and Industry Spaces at the global, regional, and local level;
• Tracking flows of knowhow in all its forms (business travels, social interrelationships between entrepreneurs, etc);
• Creating networks of related tasks and skills to estimate knockoff effects and productivity gains of automation;
• Investigating the dynamics of innovation via analysis of patents and inventions;
• Uncovering scaling laws and other growth trends able to describe the systemic increase in complexity of activities due to agglomeration, e.g. in cities;
• In general, any application of network analysis that can be used to further our understanding of economics.
We’re looking forward to your contributions!
We have published four new papers over the summer:
- New and atypical combinations: An assessment of novelty and interdisciplinarity, by M. Fontana, M. Iori, F. Montobbio, R. Sinatra, published in Research Policy
We compare different indicators of novelty and interdisciplinarity, and find that often they can’t distinguish novel and non-novel articles apart. We also find measured novelty highly overlaps measured interdisciplinarity, because the two are operationalized in similar ways.
- Mapping socioeconomic indicators using social media advertising data, by M. Fatehkia, I. Tingzon, A. Orden, S. Sy, V. Sekara, M. Garcia-Herranz, I. Weber, published in EPJ Data Science
In this paper we ask: Is it possible to estimate poverty using data from the Facebook Ad platform?
- Knowledge diffusion in the network of international business travel, by M. Coscia, F.M.H. Neffke, R. Hausmann, published in Nature Human Behavior
Read Michele’s blog post about it: http://www.michelecoscia.com/?p=1838
- Multiplex Graph Association Rules for Link Prediction, by M. Coscia and M. Szell, accepted for publication in 15th International Conference on Web and Social Media (ICWSM) 2021
Here we investigate the multiplex link prediction problem with graph association rules: Will two nodes connect, and of which type?