Data Science and Networks
Examine our series, books and journals in the field of Data Science and Networks.
Data Science and Networks
Read a blog by one of our editors
Explore our journals and articles on Data Science and Networks
Delve into Springer series and books
From our editor
Ronaldo Menezes Editor-in-Chief of our journal "Applied Network Science".
He is a Professor of Data and Network Science, Head of the Computer Science department at the University of Exeter, and Director of the BioComplex Laboratory. His research interests include Network Science, Human Dynamics and Mobility, Complex Systems, and Urban Systems.
In this blog, he writes about the COVID-19 pandemic and human mobility.
Read and share some recent content from our journals
We are showcasing a selection of issues and articles focusing on Data Science and Networks, free through 15 August.
Open access articles are freely available online on a permanent basis.
- Uncovering the internal structure of Boko Haram through its mobility patterns by Rafael Prieto Curiel, Olivier Walther & Neave O'Clery
- Crowdsourcing the Robin Hood effect in cities by Thomas Louail, et al.
- Social and economic flows across multimodal transportation networks in the Greater Tokyo Area by Aaron Bramson, et al.
- Estimation of traffic flow changes using networks in networks approaches by Jürgen Hackl & Bryan T. Adey
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Analytics for directed contact networks by George Cybenko & Steve Huntsman
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The time varying network of urban space uses in Milan by Alba Bernini, Amadou Lamine Toure & Renato Casagrandi
- AppMonitor: restricting information leakage to third-party applications by Nemi Chandra Rathore & Somanath Tripathy
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A systematic mapping on automatic classification of fake news in social media by João Victor de Souza, et al.
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Neutrality may matter: sentiment analysis in reviews of Airbnb, Booking, and Couchsurfing in Brazil and USA by Gustavo Santos, et al.
- An ego network analysis of sextortionists by Frédérique Oggier, Anwitaman Datta
& Silivanxay Phetsouvanh
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A framework for improving electoral forecasting based on time-aware polling by Alexandru Topîrceanu & Radu-Emil Precup
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A Twitter-based approach of news media impartiality in multipartite political scenes by Sotirios Gyftopoulos, et al.
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Modeling and analysis of crime prediction and prevention by Akhil Kumar Srivastav, S. Athithan & Mini Ghosh
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Ranking and grouping social media requests for emergency services using serviceability model (OA) by Hemant Purohit, Carlos Castillo & Rahul Pandey
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Tweets can tell: activity recognition using hybrid gated recurrent neural networks by Renhao Cui, Gagan Agrawal & Rajiv Ramnath
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Activeness of Syrian refugee crisis: an analysis of tweets by Karsten Ladner, Ruchishya Ramineni & K. M. George
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A novel approach to identify subtype-specific network biomarkers of breast cancer survivability by Sheikh Jubair, et al.
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Machine learning approach for wart treatment selection: prominence on performance assessment by Abinash Mishra & U. Srinivasulu Reddy
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Using Twitter for diabetes community analysis by Krunal Dhiraj Patel, et al.
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Effect of hospital architecture, computer games, and nurses’ behavior on the effectiveness of the treatment process of adolescent cancer patients by Zhuo Zheng & Saghar Samimi Sedeh
- A comparison and analysis of the Twitter discourse related to weight loss and fitness by Shabnam Shadroo, et al.
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A multi-target approach for discovery of antiviral compounds against dengue virus from green tea by Pooja Mahajan, et al.
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Two-dimensional finite element model to study the effect of periodic physical exercise on temperature distribution in peripheral regions of human limbs by Babita Kumari & Neeru Adlakha
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Using Twitter to raise the profile of childhood cancer awareness month by Mohsen Yoosefi Nejad, et al.
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An energy-efficient multi-hop routing protocol for health monitoring in wireless body area networks by Subba Reddy Chavva & Ravi Sankar Sangam
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Social-network analysis in healthcare: analysing the effect of weighted influence in physician networks by Abhinav Choudhury, Shruti Kaushik & Varun Dutt
EPJ Data Science (OA)
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In search of art: rapid estimates of gallery and museum visits using Google Trends by Federico Botta, Tobias Preis & Helen Susannah Moat
- PepMusic: motivational qualities of songs for daily activities by Yongsung Kim, Luca Maria Aiello &
Daniele Quercia
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Public debate in the media matters: evidence from the European refugee crisis by Caleb M. Koch, et al.
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Comparative analysis of layered structures in empirical investor networks and cellphone communication networks by Peng Wang, et al.
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Success and luck in creative careers by Milán Janosov, Federico Battiston & Roberta Sinatra
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Fake news propagates differently from real news even at early stages of spreading by Zilong Zhao, et al.
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Novelty and influence of creative works, and quantifying patterns of advances based on probabilistic references networks by Doheum Park, Juhan Nam & Juyong Park
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Following the footsteps of giants: modeling the mobility of historically notable individuals using Wikipedia by Lorenzo Lucchini, Sara Tonelli & Bruno Lepri
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Mapping the physics research space: a machine learning approach by Matteo Chinazzi, et al.
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Success in books: predicting book sales before publication by Xindi Wang, et al.
- A multi-structure multi-run range (MSMRR) approach for using machine learning with constrained data in pavement engineering by M K Nivedya & Rajib B Mallick
- Prediction of PM2.5 concentration based on multi-source data and self-organizing fuzzy neural network by Junfei Qiao, Zengzeng He & Shengli Du
- The paradox of big data by Gary Smith
Our book highlights in Data Science and Networks
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Explore a selection of featured books below - enjoy free access to book chapters until 15 August: |
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by Andy Lawrence This textbook presents an introduction to the use of probability in physics, treating introductory ideas of both statistical physics and of statistical inference, as well the importance of probability in information theory, quantum mechanics, and stochastic processes, in a unified manner. Free online chapter: |
by Reda Alhajj, Mohammad Moshipour & Behrouz Far (Eds.) This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas. Free online chapter: An Introductory Multidisciplinary Data Science Course Incorporating Experiential Learning |
by Michael Golosovsky This book deals with the science of science by applying network science methods to citation networks and uniquely presents a physics-inspired model of citation dynamics. This stochastic model of citation dynamics is based on a well-known copying or recursive search mechanism. Free online chapter: |
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by Moritz Helias & David Dahmen This book presents a self-contained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks. It is intended for physicists, mathematicians, and computer scientists and it is designed for self-study by researchers who want to enter the field or as the main text for a one semester course at advanced undergraduate or graduate level. Free online chapter: |
by Shi-Ju Ran, et al. Tensor network is a fundamental mathematical tool with a huge range of applications in physics, such as condensed matter physics, statistic physics, high energy physics, and quantum information sciences. This book is also useful to those who apply tensor networks in areas beyond physics, such as machine learning and the big-data analysis. Free online chapter: |
by Haitao Zhao, et al. This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. It can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence. Free online chapter: |
Citation Analysis and Dynamics of Citation Networks
Statistical Field Theory for Neural Networks
Tensor Network Contractions
Feature Learning and UnderstandingSpringer Series in Data Science and Networks
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The aim of this book series is to provide the most up-to-date research results and tutorial materials on current topics in this growing field as well as to stimulate further research interest by transmitting the knowledge to the next generation of scientists and engineers in the corresponding fields. Contact Christoph Baumann to know more about this series. |
This book series aims to provide details of blockchain implementation in technology and interdisciplinary fields such as Medical Science, Applied Mathematics, Environmental Science, Business Management, and Computer Science. Contact Loyola D'Silva to know more about this series. |
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