Projects

mdm Web: https://www.upf.edu/web/mdm-dtic/projects/
Funded by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502)
The research scope of this project lies at the intersection of two different areas: computational social science and machine learning. The main goal is to develop the required tools to analyze, model and influence social behavior in order to optimize performance of a given online platform. The project will focus in online platforms for open democracy, but other types of platforms such as news aggregators, Wikipedia or MOOCs will also be analyzed.The platform considered in this project is open source and has been adopted by the area of citizen participation and transparency of Madrid as Decide Madrid and the City Council of Barcelona (Decidim Barcelona). Our role in both platforms is to suggest and implement possible features or extensions to improve its performance. In research terms, this means that the platform can be used, not only as a source of high-­quality social data, but also, given our possibility of performing interventions, to conduct controlled experiments in which we analyze the influence of different factors in a social environment.
Web: http://medialab-prado.es/article/lineas-de-trabajo-en-torno-a-la-combinacion-de-herramientas-digitales-y-procesos-presenciales-para-la-participacion
Funded by ParticipaLab – Medialab Prado
Data analysis for citizen participation aims to address the analysis of all data flows that occur when citizens actively participate using digital networked tools.

  • The information flows of social or media networks that lead to participation.
  • The interest groups or groups that carry out campaigns to collect support.
  • The Interactions in civic tech tools: discussions, votes, supports, comments, edits, etc.

All these processes are complex and open a new field of interpretation and study of data which is the scope of this project. How to learn to improve participation based on a diagnosis based on specific and objective reasons? How to monitor participatory processes? How to visualize the effects of the changes of functionality of the tools, of the design or usability of the same? Can the visualization of data facilitate the processes of participation to the citizens?

decode Web: http://www.decodeproject.eu/
Funded by the European Commission in the H2020 “Distributed Architectures for Decentralised Data Governance” Programme
DECODE will increase digital sovereignty of European citizens by enabling them to produce, access and control their data and exchange contextualised information in real-time, and in a confidential, and scalable manner. DECODE will develop a modular privacy-aware IoT hub with a free and open source operating system backed by a state of the art blockchain infrastructure supporting smart-contracts and privacy protections.The architecture will be demonstrated through four pilots in Barcelona and Amsterdam, in the field of digital democracy, citizen sensing, and collaborative economy. The pilots will be run with the active involvement of social entrepreneurs, hackers, and makers. Innovators will be able to build solutions on top of the platform through hackathons and open challenges, while ensuring their security, resilience and privacy preserving qualities. This aims to create a decentralised innovation ecosystem that will attract a critical mass able to shift the current centralised data-driven economy towards a decentralised, sustainable and commons-based economy. DECODE puts agency and data control in the hands of citizens, to improve citizens’ well-being and society for the collective benefit of all.
lps-bigger Web: http://www.cienlpsbigger
Co-funded by the Spanish National Strategic Consortium for Technical Research
The main objective of LPS-Bigger project is the creation of the first development environment for Big Data applications. The project will follow a software product line (Línea de Producto Software – LPS). The proposed LPS will use as core assets, a set of components that cover all phases of the lifecycle of Big Data application. These components are defined, designed and developed for being incorporated into the LPS from Big Data applications in several functional and innovative market areas which will be developed within this project. These components, properly encapsulated to facilitate its reusage, will not only be used by LPS but will become an toolkit or library of components for developers.
dcent Web: http://dcentproject.eu/
Funded by the European Commission in the FP7 “Collective Awareness Platforms for Sustainability and Social Innovation” Programme
D-CENT (Decentralised Citizens ENgagement Technologies) will accelerate innovation in the use of the Internet to help communities share data and collaborate to address major societal challenges. Despite its huge potential to transform everyday democratic decision making or to enable citizens to shape their own economic destiny, today’s Internet is becoming highly centralised. D-CENT will create a bottom-up, decentralised, open platform for collective awareness based on integrating already successful open-source codebases. Its practical experiments will address:

  • Democratic engagement, building on Europe’s largest experiments in direct democracy – the Open Ministry linked into parliament in Finland, and the involvement of the whole population in shaping a new wiki-constitution in Iceland – as well as one of Europe’s most dynamic social movements, in Spain. These will show how millions of citizens can become engaged in day-to-day deliberation, and decision-making.
  • The connection of these new approaches to empowerment to economic platforms  (Freecoin).

D-CENT will provide civil society with immediately useable digital tools for social innovation and sustainability. But it will also grow longer-term alternatives to today’s highly centralised platforms and power structures.

Web: http://onodo.org/en/
Funded by CHEST (Collective enHanced Environment for Social Tasks), a collaborative project funded by the European Commission in the FP7 “Collective Awareness Platforms for Sustainability and Social Innovation” Programme
An open, replicable and collaborative platform to facilitate the analysis of networks and relationships in any field of knowledge. With Onodo users will be able to create their own project and facilitate analysis and understanding of complex information.ONODO is based on the initial development of the project Who Rules (Quién Manda), a map of political and economic power in Spain, presented as an interactive, graphical and documented repository of all ties between the most influential people in the country. ONODO will improve the current version of Quien Manda, creating a broader, state-of-the-art platform, simple to replicate in other contexts and countries and easy to use and understand for any kind of user. We will:

  • develop the platform, improving access and re-use of data, doing entity extraction and recognition, advanced network analysis and improvement of existing visualizations.
  • facilitate re-use and replication in other languages and contexts.
  • promote citizens’ and other stakeholders’ engagement and participation.
Funded by ACCIÓ, the agency for business competitiveness of the Generalitat of Catalonia.
In the last decade, social media have exploded as a key channel for the communication among people around the world. The communication/marketing industry has reacted to this trend by implementing thousands of Social Media Monitoring (SMM) tools to measure online conversations. Most tools base their algorithmics on text analytics through Natural Language Processing methods or trivial approaches that count and rank occurrences (e.g., most retweeted users, trending topics, etc.). Consequently, data visualization is mainly covered by dashboards composed of lists of ranked items, line/pie/bar charts and word/tag clouds. These techniques are typical features of media analysis but ignore the social aspect of social media. If social media allow people to interact in virtual networks, should Network Science not play a primary role in the SMM industry? KALIUM has been designed as a social media monitoring platform to solve this problem by integrating (1) Social Network Analysis and (2) rich and flexible UI, enabling users to rapidly develop end-to-end dashboards
emaps Web: http://www.climaps.org/
Funded by the European Commission in the FP7 “Science in Society” Programme
EMAPS (Electronic Maps to Assist Public Science) is a collaborative research project aiming at answering in the most innovative way the topic SiS.2011.3.0.6-1 which calls for an assessment of “the opportunities and risks in the use of the web and the social media as a meaningful information tool and for developing a participatory communication between scientists and the different publics”.

The involvement of different publics, whether scientists, journalists, activists, corporations or citizens, comes from favouring the political relevance of their disagreements through access to datasets and documentation, representation of the debates and their dynamics, etc. which digitalization now enables to map and share. This is the hypothesis EMAPS assesses, drawing on a set of theories and practices to be assembled in the project: digital methods, science and technology studies, communication design and social innovation. Six partner institutions participate, including specialists of the climate change adaptation issue. The scientific coordinator at Sciences Po, Prof. Bruno Latour, is among the researchers who created the field of science studies, and has an extensive experience in analysing technoscientific controversies. Innovations of EMAPS lie in the participation of the Young Foundation, a not-for-profit organization based in the UK; in the survey of existing experiences of online technoscientific debates; in the design of debate mapping driven by potential users’ needs; and in the assessment of the impact of our web platforms to build an open community not only of users but of contributors as well.

cenitsocialmedia Web: http://cenitsocialmedia.es/
Co-funded by the Spanish National Strategic Consortium for Technical Research
Leading companies in the field of innovation in the media sector have come together to research the new communication and business opportunities offered by social networks, in a project dubbed Social Media. The objective of Social Media is to exploit the latest social phenomenon provided by the Internet: the publication of information and opinions by online users and their growing participation in social networks. The consortium, led by Yahoo! Iberia, is made up of pioneering companies from different sectors such as marketing, advertising, communication, media-based information analysis, the general media, marketing-orientated data mining, IT, data visualisation and social networks, along with a variety of subcontracted research centres that also form part of the project framework.
smmart Web: http://aws.typepad.com/aws/2010/11/aws-start-up-challenge-2010-finalists.html
Awarded as Amazon Web Services Start-Up Challenge European Semi-finalist
SMMART (social media marketing analysis and reporting tool) is positioned in Spain in the field of corporate social reputation, measuring effectiveness of marketing campaigns, detection of new trends, monitoring of competition in the Internet and is being perceived as an excellent tool used by major companies in the country among which are telecom operators, banks, business schools, handset manufacturers, game makers, political parties, associations, etc. SMMART is evolving into a new concept which we called “Open Social CRM,” which combines concepts in monitoring tools, CRM tools, social tools, and a philosophy of open innovation.
pfc Web: http://2010.lucene-eurocon.org/meetup.html
Presented in Apache Lucene Eurocon 2010
Highly scalable system for the identification of conversations generated in the Spanish blogosphere. Big data is handled by a distributed design framework based on Hadoop and Amazon Elastic Compute Cloud. The system consists of four modules in Java:

  • Crawling: Nutch
  • Entity Extraction: XPath and HTML density approach
  • Indexing: Solr
  • Clustering: LingPipe
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