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STA

SLOVENSKA TISKOVNA AGENCIJA DOO
Country: Slovenia
4 Projects, page 1 of 1
  • Funder: European Commission Project Code: 691152
    Overall Budget: 1,314,000 EURFunder Contribution: 1,273,500 EUR

    In today's world, access to information is a decisive factor advancing industry, society and even culture. It is therefore of great importance to understand why and how some information (e.g. some memes) spreads virally with great ease, while other is met with disinterest and omission. Uncovering the reasons may allow promoting important information, like warnings about cyber-attacks, while stifle harmful rumors, such as vaccines causing autism. The aim of the project is to treat the vast complexity of such information dynamics in social systems by involving researchers in social sciences, journalism, computing, data mining and complexity science. 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.

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  • Funder: European Commission Project Code: 288342
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  • Funder: European Commission Project Code: 101086321
    Funder Contribution: 1,297,200 EUR

    In today's world, access to information thought of as the resolution of uncertainty; is often considered as a benefit or even as an indisputable human right. There is, however, the “dark side” of information: the abundance of data beyond one’s capacity to process them leads to so-called information overload (IOL). This notion had troubled mankind long before even the print was invented and examined from different points of view, ranging from neuroscience to journalism. IOL is, however, usually considered at the individual level by examining a single factor or a specific level that eventually leads to switching off an active individual. The influence of IOL appearing simultaneously at different levels, i.e., a multilevel information overload is unknown, though. These observations lead to setting the main aim of the OMINO - Overcoming Multilevel INformation Overload project in a form of the following objectives: (1) create and apply means to measure multilevel IOL in different systems as well as methods to model IOL and counter-measures to mitigate this phenomenon, (2) training and knowledge exchange on IOL between partners in different domains using expertise from universities in U.S., Singapore and Japan, (3) intersectoral knowledge transfer between academia and the media industry (Slovenian and Austrian Press Agencies) by exposing researchers to real-life problems and giving business access to innovative methods and tools for information analysis. One of the most important aspects of the undertaken research area is its interdisciplinary nature, requiring joint work of experts in different fields and topics, i.e., social sciences, neuroscience, journalism, computing, data mining and complexity science. OMINO will accelerate individual careers of involved researchers, especially early stage ones and increase their employability. The project will lay foundations for long-term collaboration by strengthening existing links between partners and creating new ones.

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  • Funder: European Commission Project Code: 101095095
    Overall Budget: 2,989,760 EURFunder Contribution: 2,989,760 EUR

    Experts, scholars, and leading political decision-makers warn that Online Social Networks (OSNs) have transformed public debate in harmful ways. Personalization algorithms, it has been argued, create so-called filter bubbles and echo chambers where users’ opinions are reinforced, amplifying processes of opinion polarisation. Despite frequent calls for interventions to minimize such undesired effects, there is no agreed-upon method for estimating the effects of changing the parameters of the design of a social network service. Crucially, the complexity of such systems makes it hard to translate results of isolated experiments into an estimate of the overall effects. The TWON project will develop a novel empirical method for systematically researching the effects of design choices of mechanisms inside OSNs, by creating digital twins of social network sites, called TWONs. The TWON can then be used to study counterfactuals, such as: How would the effects look like, had the OSN been designed differently? In order to achieve that, the TWON project will combine empirical observations of existing OSNs, theory-informed simulations, and specific case studies. These form an iterative process, in which we will build and refine the TWON. If successful, this would be a major leap towards a better understanding of platform mechanics, both for the scientific community and for societal stakeholders. The TWON project will produce evidence-based recommendations for regulatory innovations regarding OSNs and enhance digital citizenship by participatory methods. This can reduce the detrimental effects on democratic debates when platforms are primarily optimized for economic gain. TWON enables OSN research in a controlled but naturalistic environment that would not be possible relying on for-profit OSN operators. The effectiveness of the TWON method will be demonstrated in two case studies on two diametrically controversial ongoing debates: the conflict in Ukraine and COVID-19.

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