291. The false information epidemic in social media : overview of recent developments and researchBlaž Rodič, 2024, objavljeni povzetek znanstvenega prispevka na konferenci Opis: Throughout history, crises in human society have often been accompanied by unintentional (misinformation) as well as deliberate (disinformation) spread of false information, dating back to ancient Egypt. However, the rise of online social networks has brought the magnitude of the so-called 'fake news' phenomenon to an unprecedented size. The World Economic Forum identifies disinformation as one of the foremost threats to human society. In our digital society, the rapid and widespread propagation of false information poses significant challenges to democratic processes. This contribution provides an overview of research on the spread of false informationon social networks, with a focus on major global crises such as the U.S. elections, the Covid-19 pandemic, and the war in Ukraine, and presents the results of our ongoing research project in this area.
Ključne besede: social media, misinformation, disinformation, fake news, simulation modelling
Objavljeno v ReVIS: 14.04.2025; Ogledov: 262; Prenosov: 1
 Povezava na datoteko |
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293. The Role of social networks in the spread of fake newsBlaž Rodič, 2024, objavljeni znanstveni prispevek na konferenci Opis: Crises in human society have been accompanied by the deliberate and unintentional spread of false news since the time of ancient Egypt. However, the spread of misinformation has taken entirely new dimensions with the emergence of online social networks. According to the World Economic Forum, fake news represents one of the main threats to human society. The scope and speed of the dissemination of fake news and misinformation in today's world significantly negatively affect democratic processes. In this contribution, we present an overview of research on the spread of fake news on social networks, focusing on major global crises in recent times, such as the U.S. elections, the Covid-19 pandemic, and the war in Ukraine, and present the state of our ongoing research project in this field.
Ključne besede: misinformation, fake news, social networks, network diffusion, agent based modelling
Objavljeno v ReVIS: 14.04.2025; Ogledov: 369; Prenosov: 6
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294. Social media bot detection research : review of literatureBlaž Rodič, 2025, strokovni članek Opis: This study presents a review of research on social media bot detection. Social media bots are used by political and criminal actors for mass distribution of political messages, as well as rumors, conspiracy theories, and other forms of false information. Through the spread of disinformation, bots are eroding the public trust in political and media institutions and integrity of social media. We have examined recent research publication in the field of social media bot detection, including several previous reviews of bot detection research, and identified the methods used in bot detection and issues encountered by researchers. Our review was conducted through a search of 5 main bibliographical databases, which has produced a total of 534 research papers and other publications. This collection was then filtered with exclusion and inclusion criteria to isolate the most pertinent documents, resulting in a focused selection of 49 documents that were analyzed for this review. In the first part of the paper we introduce the phenomenon of fake news within social networks, its connection with social media bot activity, and conclude the introduction with issues caused or exacerbated by bots. In the main part of this paper we first present the results of statistical analysis of the reviewed documents and then introduce the field of social media bot research, followed by an overview of the issues of social media bot detection identified in the reviewed literature, including the evolution of bot concealment techniques and the methodological issues presented in some of the bot detection studies. We then proceed with an overview of the methods and results from the reviewed research papers, structured according to the main methodology used in the examined studies. Our review concludes with examination of the recent trends in social media bot development and related bot detection research.
Ključne besede: social media, social networks, social media bots, Twitter bots, bot detection, misinformation, disinformation, fake news
Objavljeno v ReVIS: 14.04.2025; Ogledov: 278; Prenosov: 1
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295. Bridging perceived and actual data quality : automating the framework for governance reliabilityTomaž Podobnikar, 2025, izvirni znanstveni članek Opis: The discrepancy between perceived and actual data quality, shaped by stakeholders’ interpretations of technical specifications, poses significant challenges in governance, impacting decision-making and stakeholder trust. To address this, we introduce an automated data quality management (DQM) framework, implemented through the NRPvalid toolkit, as a standalone solution incorporating over 100 assessment tools. This framework strengthens data quality evaluation and stakeholder collaboration by systematically bridging subjective perceptions with objective quality metrics. Unlike traditional producer–user models, it accounts for complex, multi-stakeholder interactions to improve data governance. Applied to planned land use (PLU) data, the framework significantly reduces discrepancy, as quantified by error score metrics, and directly enhances building permit issuance by streamlining interactions among administrative units, municipalities, and investors. By evaluating, refining, and seamlessly integrating spatial data into the enterprise spatial information system, this scalable, automated solution supports constant data quality improvement. The DQM and its toolkit have been widely adopted, promoting transparent, reliable, and efficient geospatial data governance.
Ključne besede: perceived and actual data quality, data quality management, DQM, quality assurance/quality control, QA/QC, spatial data quality, data quality standards, data governance, planned land use, automation, uncertainty management, geospatial
Objavljeno v ReVIS: 14.04.2025; Ogledov: 279; Prenosov: 1
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296. A framework for bridging perceived and actual quality through automation : strengthening data reliability and governanceTomaž Podobnikar, 2025, drugi sestavni deli Opis: Following spatial data capture, stakeholders often invest significant resources to meet technical specifications. This challenge arises largely from varying interpretations of established standards, resulting in data that fails to meet the requirements for ingestion into the enterprise geospatial ecosystem. A key issue lies in the discrepancy between perceived data quality – how stakeholders understand or interpret the performance of the data, which is aligned with technical specifications – and actual data quality, which reflects objective performance when properly measured. The proposed data quality management (DQM) framework addresses this discrepancy by focusing on key aspects of spatial data quality, with an automated program playing a central role in bridging this divide. The framework enhances stakeholder communication and significantly improves the reliability of data governance by providing a comprehensive evaluation of data quality. This evaluation with the outputs combining error presentation through statistics, georeferenced files, and visualization enables rapid interpretation and error resolution. When applied to planned land use (PLU) data, this solution improved efficiency, enhanced overall data quality, and ensured seamless integration into the enterprise Spatial information system. This resulted in a higher level of maturity in data quality management.
Ključne besede: quality assurance/quality control (QA/QC), continuous process improvement, spatial data quality, data steward, data governance, planned land use data, perceived vs. actual data quality, geospatial, data quality management (DQM), uncertainty management
Objavljeno v ReVIS: 14.04.2025; Ogledov: 315; Prenosov: 2
Celotno besedilo (2,66 MB) |
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