diplomsko delo
Primož Gabrovec (Author), Zoran Bosnić (Mentor), Lovro Šubelj (Co-mentor)

Abstract

Evropska unija želi v svetovnem merilu igrati pomembno vlogo na področju znanosti in inovacij. Program Obzorje 2020 je namenjen financiranju raznih projektov, pri katerih običajno sodeluje več partnerjev iz različnih držav, zato nas zanima, kakšne so lastnosti partnerjev, ki skupaj prijavljajo evropske projekte. V diplomski nalogi smo zbrali in analizirali naslednje podatke o projektih: država, iz katere posamezen partner prihaja, njihov status (vodja skupine, član), tip organizacije (univerza, raziskovalni inštitut, zasebne organizacije) in podobno. Pri obdelavi podatkov smo uporabili metode analize socialnih omrežij, s katerimi smo narisali grafe povezav med partnerji ter nato iz grafov razbrali različne lastnosti. Z metodami za detekcijo skupnosti smo nato projekte razdelili v skupine in ugotovili, kateri tipi organizacij največ sodelujejo pri posameznih projektih, s katerimi tipi projektov se ukvarjajo večje skupnosti in katere organizacije se med seboj največ povezujejo. Ugotovili smo, da ima geografska lokacija močan vpliv na vzpostavljanje partnerstev. Razvidne so tudi razlike med konzorciji, na projektih s področja znanosti in industrije so konzorciji ponavadi manjši, konzorciji, ki delajo na projektih na temo družbenih izzivov, pa ponavadi povezujejo več kot deset organizacij. Ugotovili smo tudi, da se Slovenija v primerjavi z bolj uspešnimi državami manj povezuje z evropskimi državami izven EU, kot sta Švica in Norveška.

Keywords

analiza socialnih omrežij;analiza družbenih omrežij;socialna omrežja;detekcija skupnosti;Obzorje 2020;univerzitetni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [P. Gabrovec]
UDC: 004:316.472.4(043.2)
COBISS: 169181955 Link will open in a new window
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Downloads: 5
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Other data

Secondary language: English
Secondary title: Use of social network analysis algorithms on international projects applicants' data
Secondary abstract: The European Union wants to be a major player on the global stage of science and innovation, therefore programs such as the Horizon 2020 have been created. As most applicants apply through a consortium, the common attributes of the participating organisations and/or countries are of interest. In this thesis we analysed the following attributes: the applicants' country of origin, their status within the consortium (coordinator or participant), the type of the organisation (higher education institution, research institute, private for profit entity) and similar. We used social network analysis methods on graphs of connections between partners. Community detection methods were used to divide the projects into groups and thus establish which types of organisations commonly work together on certain types of projects, which types are common among larger groups and which organisations commonly form a consortium. The results of the analysis demonstrate that geographical location plays an important role. There are also big differences between consortiums; they are usually smaller on science and industrial projects and much larger on projects about societal challenges, where it is common to see more than ten organisations working together. In addition to that, we also found that Slovenia does not have as many connections to non-EU members such as Switzerland or Norway, compared to the more successful European countries.
Secondary keywords: social network analysis;community detection;Horizon 2020;computer science;diploma;Družbena omrežja;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000468
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 91 str.
ID: 21439491