Reverse EngiNeering of sOcial Information pRocessing
EU Horizon2020 Project in the framework of Marie Skłodowska-Curie Actions
Research and Innovation Staff Exchange (RISE) Call: H2020-MSCA-RISE-2015
The general research aim of the Project is to reverse-engineer information dynamics in social
networks, such as spreading of innovations and rumors among people, viral spreading of
information in social media such as Twitter or Facebook and dynamics of news and their topics
The Project’s objectives are:
discovery and reverse-engineering the mechanisms of information spreading in social media, such as dynamics of news releases, blog and internet for posts, Twitter messages, e-mails etc.,
training and exchange of knowledge between partners in different domains coming from Warsaw University of Technology, Jozef Stefan Institute, Wroclaw University of Technology and leading world universities Stanford University, Rensselaer Polytechnic Institute, Nanyang Technological University,
bidirectional knowledge transfer between academia and media industry (Slovenian Press Agency) by exposing researchers to real-life problems and giving business access to innovative methods and tools for information analysis.
The project will be based on three pillars: data acquisition, data mining/machine learning and complex systems modeling. The specific problems addressed will include understanding rules of and predicting information spreading in different media and about different topics, finding information sources and uncovering hidden information channels. The secondments will accelerate individual careers of involved researchers, especially early stage ones. The project will lay foundations for long-term collaboration by strengthening existing links between partners and creating new ones.
RENOIR Project consists of the following Workpackages
WP1 - Knowledge and innovation exchange on data infrastructure for social information
The objective of this WP is to form a common RENOIR data infrastructure to exchange data and knowledge
related to social information and reverse engineering of information flows. The infrastructure will support
complete research cycle (hypothesis-data-model-evaluation). This WP will be led by the non-academic project partner STA (Slovenian Press Agency) who will share the developed and adapted data layer technologies with other RENOIR Partners. We expect that innovative solutions in data science technique will be elaborated during the intersectoral collaboration of the seconded staff. The solutions will be further exploited to increase portfolio services and market potential of the STA. Training on the usage of the data infrastructure will be offered by STA for academic researchers and non-academic staff. Deliverables of this WP will be inputs to tasks running in WP2 and WP3.
WP2 - Knowledge and innovation exchange on data- mining/machine- learning for reverse engineering of social information processing
The objective of this WP is to create RENOIR research components, using the platform from WP1 (data
infrastructure) using analytic techniques to reverse-engineer social processes from media data of different
kinds (main stream media, social media). The results will be used in the WP3 for various inference tasks. The aim is to use modern analytic techniques from the areas of statistical machine learning, data mining, computational linguistics, social network analysis, streaming analytics, relational learning to approach modelling of global social dynamics from several aspects
WP3 - Knowledge exchange on modeling of information inference in social networks
The objective of the Workpackage is to build a theoretical framework for reverse engineering of social information processing. The aim will be reached by developing and testing methods for inference of missing network structure and sources of information spreading in complex social networks. Additional aim is to develop data driven and analytical models of information spreading basing on data collected in WP1 and processed by methods developed in WP2. Attention will be given to networks displaying structure changing in time (temporal networks) as well as multi-layer and modular networks. Complementary expertise of different Partners on various modeling techniques will be used to build this framework. Training will be offered for young researchers visiting Partners Institutes.
WP4 - Training, sharing and dissemination of knowledge
The objective of this WP is to enhance and to methodize sharing and disseminating the knowledge and results
that come from other work packages of the project. The activities that are planned in WP4 cover sharing the video lectures, publishing the results in open access journals, as well as establishing a scientific web platform for collaboration and dissemination. Moreover, it is planned to organize a number of project-related or strictly scientific activities that will additionally support the dissemination of the results.
WP5 - Management, Communication
Coordinate the financial and administrative aspects of the Project. Ensure an appropriate and functioning networking between Participants. Coordinate the Participants such that the Project deliverables produced on time. Coordinate the protection, use and dissemination of the knowledge generated.
On 23 May, PhD student from WUT gave a talk entitled "Heider balance in bilayers" on Network Science Short-talks at University…