Title: Opening up New Channels for Scholarly Review, Dissemination, and Assessment

Authors: Edit Gorogh:University of Gottingen; Michela Vignoli:Austrian Institute of Technology Vienna; Eleni Toli:University of Athens; Electra Sifacaki:University of Athens;
Peter Kraker:Know Center; Ilire Hasani-Mavriqi:Know Center; Stephan Gauch:German Centre for Higher Education Research and Science Studies (DZHW); Daniela Luzi:Consiglio Nazionale delle Ricerche Rome; Mappet Walker:Frontiers; Clemens Blümel:German Centre for Higher Education Research and Science Studies (DZHW) & Humboldt University Berlin

Abstract: The growing dissatisfaction with the traditional scholarly communication process and publishing practices as well as increasing usage and acceptance of ICT and Web 2.0 technologies in research have resulted in the proliferation of alternative review, publishing and bibliometric methods. The EU-funded project OpenUP addresses key aspects and challenges of the currently transforming science landscape and aspires to come up with a cohesive framework for the review-disseminate-assess phases of the research life cycle that is fit to support and promote open science. The objective of this paper is to present first results and conclusions of the landscape scan and analysis of alternative peer review, altmetrics and innovative dissemination methods done during the first project year.

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Title: Before the Sense of ‘We’: Identity Work as a Bridge from Mass Collaboration to Group Emergence

Authors: Arto Lanamaki:Interact Research Unit, University of Oulu; Juho Lindman:University of Gothenburg / Chalmers

Abstract: Individuals engaged in mass collaboration in Wikipedia may join to work recurrently with the same partners. It may well be that a significant portion of Wikipedia content is produced this way. Therefore, it is important to study how such groups emerge. In this paper, we argue how such recurrence may involve identity work that creates a sense of ‘we-ness.’ We provide a case from Wikipedia, focusing on how individual Wikipedians came together to work on a collaborative Feature Article task. Furthermore, the same people came together in other content collaborations, and they identified themselves as a group. The findings suggest that identity work can bridge mass collaborations to the emergence of smaller-scale sustained groups. Our theoretical contribution brings together research streams on mass collaboration, group dynamics, and identity. This offers interesting pathways for further research.

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Title: An end-to-end learning solution for assessing quality of Wikipedia articles

Authors: Quang-Vinh Dang:University de Lorraine; Claudia-Lavinia Ignat:INRIA

Abstract: Wikipedia is considered as the largest knowledge repository in the history of humanity and plays a crucial role in modern daily life. Assigning the correct quality class to Wikipedia articles is an important task in order to provide guidance for both authors and readers of Wikipedia. The manual review cannot cope with the editing speed of Wikipedia. An automatic classification is required to classify the quality of Wikipedia articles. Most existing approaches rely on traditional machine learning with manual feature engineering, which requires a lot of expertise and effort. Furthermore, it is known that there is no general perfect feature set because information leak always occurs in feature extraction phase. Also, for each language of Wikipedia, a new feature set is required.

In this paper, we present an approach relying on deep learning for quality classification of Wikipedia articles. Our solution relies on Recurrent Neural Networks (RNN) which is an end-to-end learning technique that eliminates disadvantages of feature engineering. Our approach learns directly from raw data without human intervention and is language-neutral. Experimental results on English, French and Russian Wikipedia datasets show that our approach outperforms state-of-the-art solutions.

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Title: How are Open Source Practices Possible within a Medical Diagnostics Company? Developing and Testing a Maturity Model of Inner Source Implementation

Authors: Remo Eckert:University of Bern; Sathya Kay Meyer:University of Bern; Matthias Stuermer:University of Bern

Abstract: Open Source Software (OSS) development has seen a considerable increase in attention over the last few years. The success of various OSS projects, such as Linux and Apache, is now widely recognized. Many organizations have shown interest not only in using OSS, but also in applying the underlying collaborative practices within their internal software development activities; this phenomenon is known as Inner Source. By combining best practices of OSS development from the current Inner Source literature, we develop a new model that allows us to rate an organization’s maturity level regarding the adoption of Inner Source. By testing our model within a medical diagnostics corporation, we present various insights on Inner Source efforts and how Inner Source can improve software development.

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Title: On the Relationship between Newcomer Motivations and Contribution Barriers in Open Source Projects

Authors: Christoph Hannebauer:Universitat Duisburg-Essen; Volker Gruhn:Universitat Duisburg-Essen

Abstract: There has been extensive research on the the factors that motivate software developers to contribute to an Open Source Software (OSS) project. Contribution barriers are the counterside to motivations and prevent newcomers from joining the OSS project. This study searches for relations between motivations and contribution barriers with a web-based survey of 117 developers who had recently contributed their first patch to either Mozilla or GNOME.

The results substantiate the hypothesis that newcomers’ motivations mirror their mental models of the OSS project they are going to contribute to, and that the mental model determines the impact of contribution barriers. More generally, we propose a new model for the joining process to an OSS project that takes social properties, motivations, and contribution barriers
into account.

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Title: What do Wikidata and Wikipedia have in common? An analysis of their use of external references

Authors: Alessandro Piscopo:University of Southampton; Pavlos Vougiouklis:University of Southampton; Lucie-Aimee Kaffee:University of Southampton; Christopher Phethean:University of Southampton; Jonathon Hare:University of Southampton; Elena Simperl:University of Southampton

Abstract: Wikidata is a community-driven knowledge graph, strongly linked to Wikipedia. However, the connection between the two projects has been sporadically explored. We investigated the relationship between the two projects in terms of the information they contain by looking at their external references. Our findings show that while only a small number of sources is directly reused across Wikidata and Wikipedia, references often point to the same domain. Furthermore, Wikidata appears to use less Anglo-American-centred sources. These results deserve further in-depth investigation.

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