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Abstract: Managing employee emotions can lead to an improvement in the corporate climate and therefore to better cohesion of the corporate social network. In reality with many employees, especially those where people are spread over vast territories, the difficulties in detecting emotions become greater. Hypothesizing the usefulness of emoji-emoticons to simplify the recognition of emotions even in complex situations, we have carried out a literature review of the scientific articles which talk about emotions and emoji-emoticons. Our job consisted in researching, cataloguing and summarizing the main studies done and published by researchers in the last ten years concerning emotions and the use of emojis as a tool for the discovery and understanding of emotions in corporate working groups, to then make a briefanalysis. Much research has been done and many methods have been developed in the field of emotional-sentimental detection, just as there is much research relating to the generic use of emojis, in general, and in the corporate field. Unfortunately, we have found few studies regarding the use of emojis for emotion recognition and identification in the workplace. As a result, we have found scientific evidence of the importance of emotions in companies, noting that the different types of graphic inserts (emoji-emoticons) can be a valid support tool for human resources for detecting and analysing employee emotions. We believe we have achieved the goal of our work in providing concrete help with this literature review for future scientific developments in this field
Keywords: corporate social network, Emoji, emoticons, human resources, organizational climate, quality of work, well-being
Published in ReVIS: 19.05.2025; Views: 244; Downloads: 0

Abstract: 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.
Keywords: 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
Published in ReVIS: 14.04.2025; Views: 324; Downloads: 2
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Keywords: quality of work, healthcare workers, human resources economics, public sector economics, factor analysis, comparative analysis
Published in ReVIS: 02.02.2024; Views: 983; Downloads: 16
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