Special Issue "Information Processing and Management for Large and Complex Networks"
Deadline for manuscript submissions: 28 February 2021.
Interests: network visualization and visual analytic; large-scale graph processing; graph drawing and computational geometry; algorithm engineering
Interests: graph drawing; information visualization; computational geometry; algorithm engineering
Interests: big data; creativity and innovation management; social network analysis; semantic analysis
Network-based models are pervasive in many fields of science and technology, as they naturally capture relationships between entities. The study of relationships emerged as a pivotal addition to standard social and behavioral research, going beyond the single attributes of the social units. Indeed, networks (or graphs) are widely used to model relational data in a variety of application domains, including social sciences, economy and finance, information and homeland security, management, biology, computer networks, marketing, and software design. With the increasing amount of relational data generated every day, processing, managing, and analyzing large-scale graphs have become prominent problems in data science, which pose several challenges ranging from the design of efficient graph algorithms to the development of scalable and effective systems.
This special issue calls for papers that contribute to the multifaceted research on processing, managing, and analyzing large and complex networks. Interested authors are invited to contribute their original, unpublished work. Topics of interest include, but are not limited to, the following:
- Management information systems
- Big network data management
- Large-scale graph processing algorithms and systems
- Parallel and distributed graph algorithms
- Strategic information systems
- Decision support systems
- Graph drawing and network visualization techniques
- Human-computer interaction for network analysis
- Graph benchmarks and generators
Dr. Fabrizio Montecchiani
Prof. Dr. Walter Didimo
Dr. Andrea Fronzetti Colladon
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Affrication: 1 MIT Center for Collective Intelligence, 245 First Street, 02142, Cambridge, MA, USA.
2 School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510275, China.
Title: E-Mail Networking and Body Language Predict Risk-taking Attitude
Abstract: As the Enron scandal and Bernie Madoff’s pyramid scheme have shown, individual attitude towards ethical risks can have a huge impact on society at large. In this paper, we compare risk-taking attitudes assessed with the Domain-Specific Risk-Taking (DOSPERT) survey with individual e-mail networking patterns and body language measured with smartwatches. We find that e-mail communication signals such as network structure and dynamics, and content features as well as real-world behavioral signals measured through a smartwatch such as heart rate, acceleration, and mood state demonstrate strong correlation with individual risk-preference in the different domains of the DOSPERT survey. For instance, we found that people with higher degree centrality in the e-mail network show higher likelihood to take social risks, while using language expressing a ‘you live only once’ attitude indicates lower willingness to take risks in some domains. Furthermore, we built a regression model to validate the predictive power of these signals toward a person’s risk-preference.