@article{RykovaStiebenDostovalovaetal.2023, author = {Rykova, Eugenia and Stieben, Christine and Dostovalova, Olga and Wieker, Horst}, title = {Connected Driving in German-Speaking Social Media}, series = {Social Sciences}, volume = {12}, journal = {Social Sciences}, number = {1}, publisher = {MDPI}, issn = {2076-0760}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-16969}, year = {2023}, abstract = {Intelligent transportation systems (ITS) have been steadily becoming part of our reality. For their successful integration, studying and understanding public opinions and acceptance is important. Social media platforms offer an extensive opportunity for opinion mining. While there have been studies on people's attitudes towards automated driving, another important ITS concept—connected driving—has received little to no attention. In the current study, data on how connected driving is represented and perceived were collected from German(-speaking) Reddit and Twitter. In relevant Reddit entries, the necessity of communication between vehicles was discussed almost exclusively in the context of automated driving. On Twitter, mostly shared news and information on the topic are presented, while the number of personal opinions is low. The most concerning subtopic seems to be cybersecurity, which reflects a general trend of data protection issues discussed in society.}, language = {en} } @incollection{MoshnikovRykova2025, author = {Moshnikov, Ilia and Rykova, Eugenia}, title = {Collecting minority language data from Twitter (X): A case study of Karelian}, series = {Exploring digitally-mediated communication with corpora : Methods, analyses, and corpus construction}, booktitle = {Exploring digitally-mediated communication with corpora : Methods, analyses, and corpus construction}, editor = {Cotgrove, Louis and Herzberg, Laura and L{\"u}ngen, Harald}, publisher = {De Gruyter Brill}, isbn = {978-3-11-143401-8}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-20583}, publisher = {Technische Hochschule Wildau}, pages = {163 -- 186}, year = {2025}, abstract = {The visibility of an endangered language online plays a crucial role in language revitalisation. The internet offers a new domain for using minority languages, especially for speakers living outside the language communities. This article investigates Karelian language visibility on X, formerly known as Twitter, and describes the first corresponding data collection using language-related keywords and hashtags. In total, 2,625 entries written fully or partially in Livvi, South and Viena Karelian were scraped with Postman API. The visibility of Karelian on Twitter (X) has been increasing considerably in the past few years, with Livvi-Karelian being the most prominent dialect. Automatic language detection was tested on such data for Karelian for the first time, and allows the identification of Livvi-Karelian (or a mix of dialects that include Livvi-Karelian) with 99.7\% sensitivity, and South Karelian and Viena Karelian as Livvi-Karelian with 90\% and 73.8\% sensitivity, respectively. The entries were also analysed thematically, and 10 major topics were identified. Since the data was collected using keywords and hashtags related to the Karelian language itself, most of the entries are related to the language and vocabulary in sense of translation or language learning. Language status and policy is another important topic identified in the data. Although language-related topics are the most popular, there are a substantial number of entries on eight further topics. Excluding citations from religious texts and media headlines, 751 Twitter (X) entries could be used for linguistic and sociological research. Further data collection considerations are also discussed.}, language = {en} } @article{WagenknechtWoodsGarciaSanzetal.2021, author = {Wagenknecht, Katherin and Woods, Tim and Garc{\´i}a Sanz, Francisco and Gold, Margaret and Bowser, Anne and R{\"u}fenacht, Simone and Ceccaroni, Luigi and Piera, Jaume}, title = {EU-Citizen.Science: A Platform for Mainstreaming Citizen Science and Open Science in Europe}, series = {Data Intelligence}, volume = {3}, journal = {Data Intelligence}, number = {1}, issn = {2641-435X}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-14113}, pages = {136 -- 149}, year = {2021}, abstract = {Citizen Science (CS) is a prominent field of application for Open Science (OS), and the two have strong synergies, such as: advocating for the data and metadata generated through science to be made publicly available [1]; supporting more equitable collaboration between different types of scientists and citizens; and facilitating knowledge transfer to a wider range of audiences [2]. While primarily targeted at CS, the EU-Citizen. Science platform can also support OS. One of its key functions is to act as a knowledge hub to aggregate, disseminate and promote experience and know-how; for example, by profiling CS projects and collecting tools, resources and training materials relevant to both fields. To do this, the platform has developed an information architecture that incorporates the public participation in scientific research (PPSR)—Common Conceptual Model①. This model consists of the Project Metadata Model, the Dataset Metadata Model and the Observation Data Model, which were specifically developed for CS initiatives. By implementing these, the platform will strengthen the interoperating arrangements that exist between other, similar platforms (e.g., BioCollect and SciStarter) to ensure that CS and OS continue to grow globally in terms of participants, impact and fields of application.}, language = {en} } @article{FuhrmannSchollBruggemann2017, author = {Fuhrmann, Frauke and Scholl, Margit and Bruggemann, Rainer}, title = {How Can the Empowerment of Employees with Intellectual Disabilities Be Supported?}, series = {Social Indicators Research}, journal = {Social Indicators Research}, issn = {1573-0921}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-10066}, year = {2017}, abstract = {The project "Barrier-reduced Machines in Innovative Interaction" (iBaMs) was aimed at enabling employees with intellectual disabilities to extend their range of tasks and to increase their level of responsibility. This goal is to be achieved by an assistive accessible control panel for the operation of complex computer-controlled machines. Therefore, users' needs and skills as well as design requirements had to be specified in the project. The result is a concept for an assistive control panel whose display interface can be tailor-made to individual needs. Furthermore, indicators for characterizing user profiles and control panels were identified, and a concept was developed of how control panels can be determined and matched to the needs and preferences of individual employees. The complexity in recognizing the requirements of people with intellectual disabilities in a digital world is mapped onto a complex interaction of two sets of indicators—namely social indicators and technical indicators describing control panels. Guidelines on how the results can be evaluated are presented using plausible but fictitious data.}, language = {en} }