Nina Rizun

Gdansk University of Technology, Department of Applied Informatics in Management, Adjunct

Gdansk University of Technology, Management and Economics, Adjunct

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Papers by Nina Rizun

Prioritising national healthcare service issues from free text feedback – A computational text analysis & predictive modelling approach

Decision Support Systems, 2024

Patient experience surveys have become a key source of evidence for supporting decision-making an... more Patient experience surveys have become a key source of evidence for supporting decision-making and continuous
quality improvement within healthcare services. To harness free-text feedback collected as part of these surveys
for additional insights, text analytics methods are increasingly employed when the data collected is not amenable
to traditional qualitative analysis due to volume. However, while text analytics techniques offer good predictive
capabilities, they have limited explanatory features often required in formal decision-making contexts, such as
programme monitoring or evaluation. To overcome these limitations, this study integrates computational text
and predictive modelling as part of a Computational Grounded Theory method to determine the effect of quality
gaps in care dimensions and their prioritisation from free-text feedback. The feedback was collected as part of a
national survey to support decisions on continuous improvement in Maternity Services in Ireland. Our approach
enables (1) operationalising the service quality lexicon in the context of maternity care to explain the effect of
quality gaps in care dimensions on overall satisfaction from free-text comments; and (2) extending the service
quality lexicon with two organisational and political decision-making concepts: “Salience” and “Valence”, for
prioritising perceived quality gaps. These methodological affordances enable the extension of service quality
theory to explicitly support the prioritisation of improvement decisions which before now required additional
decision frameworks. Results show that tangibles-, process-, and reliability-related care issues have the highest
importance in our study context. We also find that hospital contexts partly determine the relative importance of
gaps in care dimensions.

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Impact of information systems (IS) infusion on Open Government Data (OGD) adoption

Digital Policy, Regulation and Governance, 2024

Purpose-This study aims to underline the possible influence of the moderator, information systems... more Purpose-This study aims to underline the possible influence of the moderator, information systems (IS) infusion, on Open Government Data (OGD) adoption and usage. Design/methodology/approach-Using the partial least squares-structural equation modeling methodological approach, the adapted unified theory of acceptance and use of technology (UTAUT) model has been used for understanding the role of the moderating variable, namely, IS infusion. Findings-Findings show that the moderating impact of IS infusion is positively significant with respect to the performance expectancy-behavioral intention relationship thereby bolstering the impact on users' perception of OGD visa -vis work/academics performance and negatively significant for social influence-behavioral intention, information quality-behavioral intention, thereby clinching the fact that with the increased engagement and involvement of OGD in the everyday life of the user, the role of significant others and information quality gets least significant. Originality/value-Extant OGD-focused research has underscored the impact of different variables as far as OGD adoption and usage is concerned; the present study seeks to add on to the extant literature by understanding the implications of IS infusion on the adapted UTAUT model constructs and behavioral intention relationships.

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Identification of Public Service Logic (PSL) and Public Service Motivation (PSM) elements in Open Government Data (OGD) initiatives

Electronic Journal of Information Systems in Developing Countries, 2023

While previous research on Open Government Data (OGD) has primarily focused on reuse and adoption... more While previous research on Open Government Data (OGD) has primarily focused on reuse and adoption, this study aims to explore the implications of the Public Service Logic (PSL) and Public Service Motivation (PSM) dimensions in the context of OGD initiatives. This study is contextualized in Tanzania wherein the OGD initiatives are at an evolving stage. For the present study, the perspectives of the 15 public officials involved in the management of the OGD initiatives are being solicited. Findings underscore the need for furthering the marketing and refurbishing the OGD initiatives' quality alongside the increased involvement of the stakeholders to engage in value co-creation. Furthermore, as a study contextualized in a developing country to understand the involvement of the public personnel in the refurbishment of the OGD initiatives, the study contributes to the extant OGD literature while identifying the OGD publisher-side challenges and strengths in a still-evolving OGD initiative. Finally, with its societal implications in terms of the impact on societal stakeholders' engagement with OGD given the PSL-PSM of the public officials, the study's relevance is also clinched

Improving the Accuracy in Text Classification Methodology in Light of Modelling the Latent Semantic Relations

The research presents the Methodology of Improving the Accuracy in Text Classification in Light o... more The research presents the Methodology of Improving the Accuracy in Text Classification in Light of Modelling the Latent Semantic Relations (LSR). The aim of this Methodology is to find the ways of eliminating the Limitations of Discriminant and Probabilistic methods for LSR revealing and customizing the Text Classification Process to the more accurate recognition of the text tonality. This aim should be achieved by using the knowledge about the text’s Hierarchical Semantic Context in the form of Corpora-based Hierarchical Sentiment Dictionary. The main scientific contribution of this research is the following set of approaches to improve the qualitative characteristics of Text Classification process: combination of the Discriminant and Probabilistic methods allowing to decrease the influences of the Limitations of these methods on the LSR revealing process; considering each document as a complex structure allowing to estimate documents integrally by separated classification of...

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Building confidence and trust in Ireland's National Maternity Services Workforce -What matters most and how

by Nina Rizun and Adegboyega Ojo

Health policy, 2023

National surveys on care experiences are increasingly adopted as regulatory mechanisms for improv... more National surveys on care experiences are increasingly adopted as regulatory mechanisms for improving care quality and increasing public trust in healthcare services. Based on data collected as part of Ireland's 2020 National Maternity Experience Survey, this study investigates care-related factors that contribute most to confidence and trust in the professional workforce (or carers) within Irish maternity services. The survey covered the full spectrum of maternity care and received 3,206 responses which were analysed using structural equation modelling. Results show that trust in carers may be enhanced through greater attention to the quality of interpersonal aspects of maternity care in a few core areas. We found that factors related to dignity and respect (β=0.270), involvement in decision-making (β=0.186), pain management (β=0.172), and communication (β=0.151) are core determinants of confidence and trust in the professional workforce of maternity services. Perceived quality of care in these four aspects increased on average, with the women's age. Women under 29 rated their experiences in these areas as significantly lower than the average. Women with a disability also rated their experiences significantly lower than average in three core areas. Our results suggest that trustworthy, equitable, and high-quality maternity care requires ongoing development of interpersonal skills within the maternity services professional workforce particularly in caring for younger women (under 29 years) and those with a disability.

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A framework of open government data (OGD) e-service quality dimensions with future research agenda

Records Management Journal, 2023

Purpose – This research paper aims to present a framework of open government data (OGD) relating ... more Purpose – This research paper aims to present a framework of open government data (OGD) relating to e-service quality dimensions. In addition, it provides a research agenda for the e-service delivery of OGD.
Design/methodology/approach – A literature review pertaining to e-service quality with special reference to e-government was delivered to deduce the key dimensions of e-service quality for OGD.
Findings – Five e-service quality dimensions of OGD are identified in the study; website design, fulfilment, service provision to the user while interfacing with the OGD Web portal, service provision to the user during and after the value-creation and innovation period and security/privacy. To further OGD re-use for value creation and innovation, it is important that the e-service quality dimensions are built into all OGD
programmes by public authorities.
Originality/value – Hitherto, extant research has focused on the data quality dimensions of OGD, but the dimensions linked with e-service have not been explored. This study seeks to fill this gap and, in addition, suggests further research requirements in this field

Assessing the failure of Open Government Data initiatives in Brazil

by Nina Rizun and Guillherme Wiedenhoft

THE ELECTRONIC JOURNAL OF INFORMATION SYSTEMS IN DEVELOPING COUNTRIES, 2023

While assessing the potential of a particular digital innovation initiative, especially when it h... more While assessing the potential of a particular digital innovation initiative, especially when it has implications for a range of societal stakeholders, it becomes pertinent to understand the possible bottlenecks in its acceptability as well. In this regard, the present study seeks to understand how the Open Government Data (OGD) initiatives in Brazil are being confronted with bottlenecks in terms of their execution and acceptability. This exploratory study adopts a qualitative cross-sectional research approach wherein interviews are being conducted with 11 managers working in public organizations and are directly associated with the OGD initiatives. Findings from the interview responses delineate internal and external factors, resource availability, data maintenance, and lack of knowledge as the key determinants for the bottlenecks associated with the execution and acceptability of OGD initiatives by the societal stakeholders. The study's originality lies in its theoretical contribution towards an understanding of how a novel digital innovation-OGD, in the present case-is fraught with impediments in terms of its execution and acceptability. The study concludes with directions for further research and practitioner implications.

ChatGPT application vis-a-vis Open Government Data (OGD): Capabilities, Public Values, Issues and a Research Agenda

Electronic Government. EGOV 2023. Lecture Notes in Computer ScienceEdition: Volume 14130, 2023

As a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the ac... more As a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the academic, medicine, law, computing or other sectors, but also for the public sector-case in point being the Open Government Data (OGD) initiative. However, though there has been some limited (as this topic is quite new) research concerning the capabilities ChatGPT in these sectors, there has been no research about the capabilities it can provide to government concerning its wide range of functions and activities. This paper contributes to filling this gap by investigating the capabilities that the ChatGPT can provide concerning one of most recently initiated and novel, and at the same time most promising, activities of government that aims to fuel the emerging data economy and society: the opening of large amounts of government data; furthermore, we investigate the public values that can be promoted through the use of ChatGPT in the area of OGD by both the data publishers as well as their users. At the same time, we investigate the issues that the use of ChatGPT in the area of OGD can pose, which can reduce the capabilities identified as aforesaid as well as the benefits and public values that can be generated from them. For these purposes interviews with 12 experts have been conducted and their responses have been analyzed. Finally, based on our findings we have developed a research agenda concerning the exploitation of ChatGPT application in the OGD domain.

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Towards High-Value Datasets determination for datadriven development: a systematic literature review

by Nina Rizun, Anastasija Nikiforova, and Magdalena Ciesielska

Electronic Government. EGOV 2023. Lecture Notes in Computer Science, vol 14130, 2023

Open government data (OGD) is seen as a political and socioeconomic phenomenon that promises to p... more Open government data (OGD) is seen as a political and socioeconomic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles, but also be of value, i.e., of interest for reuse by the end-user. This refers to the notion of "high-value dataset" (HVD), recognized by the European Data Portal as a key trend in the OGD area in 2022. While there is a progress in this direction, e.g., the Open Data Directive, incl. identifying 6 key categories, a list of HVDs and arrangements for their publication and re-use, they can be seen as "core" / "base" datasets aimed at increasing interoperability of public sector data with a high priority, contributing to the development of a more mature OGD initiative. Depending on the specifics of a region and country-geographical location, social, environmental, economic issues, cultural characteristics, (under)developed sectors and market specificities, more datasets can be recognized as of high value for a particular country. However, there is no standardized approach to assist chief data officers in this, and there is a clear lack of conceptualizations for the determination of HVD and systematic oversight. In this paper, we present a systematic review of existing literature on the HVD determination, which is expected to form an initial knowledge base for this process, including used approaches and indicators to determine them, data, stakeholders.

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Why do Open Government Data initiatives fail in developing countries? A root cause analysis of the most prevalent barriers and problems

THE ELECTRONIC JOURNAL OF INFORMATION SYSTEMS IN DEVELOPING COUNTRIES, 2023

Open government data (OGD) include the provision of government data, which have so far been reser... more Open government data (OGD) include the provision of government data, which have so far been reserved for the provision of public utilities and services, wherein different stakeholders may create value out of the same source. Recently, OGD initiatives around the world have dampened or were found to be inadequate for one or other reasons. The present study seeks to underline the root causes behind these inade

Information Scent and Open Government Data (OGD) engagement: Research agenda

International Conference on Theory and Practice of Electronic Governance (ICEGOV 2023), 2023

Visa -vis the digital innovation, i.e. Open Government Data (OGD), in the annals of public admini... more Visa -vis the digital innovation, i.e. Open Government Data (OGD), in the annals of public administration, the impetus upon user engagement holds eminence given the possibilities unleashed via value derivation. However, user engagement depends to a large extent to which OGD platforms deliver in terms of information expectations of the user. In this vein, the significance of "information scent", i.e. the propensity of a user to dig deeper into a web portal based on the quality aligned with the intrinsic goal of the user, assumes importance for facilitating optimum user engagement with the OGD portal. Drawing inferences from the experts' opinion, this study seeks to present possible research themes around this edifice. Given that OGD-research has underscored the need for website maintenance in terms of provisioning quality OGD and conducive portal features for furthering user engagement, the significance of information scent via OGD portals for consistent user engagement merits consideration for furthering the contours of OGD literature.

Do personality traits influence the user’s behavioral intention to adopt and use Open Government Data (OGD)? An empirical investigation

Telematics and Informatics, 2023

Do personality traits influence the user's behavioral intention to adopt and use Open Government ... more

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How do personality traits influence Open Government Data (OGD) adoption and usage? Investigating the indirect and moderating effects

24th Annual International Conference on Digital Government Research - Together in the unstable world: Digital government and solidarity (DGO 2023), 2023

Quality. Agreeable people are more likely to voluntarily use OGD. An individual's conscientiousne... more Quality. Agreeable people are more likely to voluntarily use OGD. An individual's conscientiousness improves their perception of factors related to OGD quality. Excessive emotionality leads to a more critical perception of systems and information quality issues. Our findings also attest to the moderating impact of Honesty-Humility across Information Quality-Behavioral Intention positively; Extraversion across Information Quality-Behavioral Intention negatively and Extraversion across Trust-Behavioral Intention positively. Honesty turns out to be important for considering Information Quality vis-à-vis OGD adoption and usage but whilst extroverts are concerned about Information Quality, i.e. flawless information retrieval via OGD sources, Introverts are concerned about OGD trustworthiness, i.e. credible OGD for its adoption and usage and Extroverts find the OGD reliable and credible. With pointers for further research across the personality traits-OGD adoption and usage theme, the study closes with practitioner implications. CCS CONCEPTS • Computing in other domains • Computing in government • Open Government Data

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Creating a Thesaurus "Crime-Related Web Content" Based on a Multilingual Corpus

Proceedings of the 7th International Conference on Computational Linguistics and Intelligent Systems. Volume II: Computational Linguistics Workshop, 2023

An overview of the most common ontological resources and methods of their construction and applic... more An overview of the most common ontological resources and methods of their construction and application is given. For purposes of scientific research we analyzed the characteristics of ontologies in the public domain and corpus containing criminal context. Additionally, we have recently developed a Flask-based web application that generates ontologies using the Anytree library. The authors also developed a multilingual basic ontology called "Illegal Web content" based on a corpus of texts in criminal context in English, Ukrainian, Kazakh and Russian languages. The development of this ontology was motivated by the need for effective analysis and prevention of criminal activities based on textual information disseminated on the internet. The newly developed web application allows users to create ontologies by importing text files in different languages, and then automatically generates an ontology based on the text. The application is user-friendly, and allows users to customize the ontology by adding or removing nodes, changing the labels of nodes and edges, and setting the weight of edges. Overall, the development of the "Illegal Web content" ontology and the web application represents a significant contribution to the field of ontology development and text processing for criminal investigation and prevention. The main characteristics of the Web application, including its ease of use and customizability, make it a valuable tool for researchers and practitioners alike.

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Application of Text Analytics in Public Service Co-Creation: Literature Review and Research Framework

DG.O 2023: The 24th Annual International Conference on Digital Government Research (dg.o 2023), 2023

The public sector faces several challenges, such as a number of external and internal demands for... more The public sector faces several challenges, such as a number of external and internal demands for change, citizens' dissatisfaction and frustration with public sector organizations, that need to be addressed. An alternative to the traditional top-down development of public services is co-creation of public services. Co-creation promotes collaboration between stakeholders with the aim to create better public services and achieve public values. At the same time, data analytics has been fuelled by the availability of immense amounts of textual data. Whilst both co-creation and TA have been used in the private sector, we study existing works on the application of Text Analytics (TA) techniques on text data to support public service co-creation. We systematically review 75 of the 979 papers that focus directly or indirectly on the application of TA in the context of public service development. In our review, we analyze the TA techniques, the public service they support, public value outcomes, and the cocreation phase they are used in. Our findings indicate that the TA implementation for co-creation is still in its early stages and thus

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A Parallel Corpus-Based Approach to the Crime Event Extraction for Low-Resource Languages

IEEE Access, 2023

These days, a lot of crime-related events take place all over the world. Most of them are reporte... more These days, a lot of crime-related events take place all over the world. Most of them are reported in news portals and social media. Crime-related event extraction from the published texts can allow monitoring, analysis, and comparison of police or criminal activities in different countries or regions. Existing approaches to event extraction mainly suggest processing texts in English, French, Chinese, and some other resource-rich and well-annotated languages. This paper presents a parallel corpus-based approach that follows a closed-domain event extraction methodology to event extraction from web news articles in lowresource languages. To identify the event, its arguments, and the arguments' roles in the source-language part of the corpus we utilize an enhanced pattern-based method that involves the multilingual synonyms dictionary with knowledge about crime-related concepts and logic-linguistic equations. The event extraction from the target-language part of the corpus uses a cross-lingual crime-related event extraction transfer technique that is based on supplementary knowledge about the semantic similarity patterns of the considered pair of languages. The presented approach does not require a preliminarily annotated corpus for training making it more attractive to low-resource languages and allows extracting TRANSFER, CRIME, and POLICE types of events and their seven subtypes from various topics of news articles simultaneously. Implementation of our approach for the Russian-Kazakh parallel corpus of news portals articles allowed obtaining the F1measure of crime-related event extraction of over 82% for the source language and 63% for the target language.

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Side Effects of National Immunization Program: E-Governance Support Toward Elders' Digital Inclusion

Proceedings of the Annual Hawaii International Conference on System Sciences, 2022

In response to the coronavirus pandemic, the European Union (EU) governments develop policies to ... more In response to the coronavirus pandemic, the European Union (EU) governments develop policies to regulate exclusive health protection actions that consider societal needs with the emphasis on elders. Given that the EU vaccination strategy uses a centralized ICT-based approach, there is little guidance on how seniors are included in national immunization programs (NIP). In this paper, we addressed a knowledge gap of the side effects of egovernance of NIP for the elderly. To fill this gap, we identified 40 side effects by analyzing online textual opinions (tweets, comments, articles) that express public perception regarding the results of the Polish NIP implementation to seniors' digital inclusion, categorized them into 8 categories and assign them to four e-governance functions. The main contribution of this paper is a better understanding of the digital divide and to provide guidelines for government policy improvement.

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Enabling Deeper Linguistic-Based Text Analytics—Construct Development for the Criticality of Negative Service Experience

IEEE Access, 2019

Significant progress has been made in linguistic-based text analytics particularly with the incre... more Significant progress has been made in linguistic-based text analytics particularly with the increasing availability of data and deep learning computational models for more accurate opinion analysis and domain-specific entity recognition. In understanding customer service experience from texts, analysis of sentiments associated with different stages of the service lifecycle is a useful starting point. However, when richer insights into issues associated with negative sentiments and experiences are desired to inform intervention, deeper linguistic analyses such as identifying specific touchpoints and the context of the service users become important. While research in this direction is beginning to emerge in some domains, we are yet to see similar efforts in the domain of healthcare. We present in this paper the results from our construct development effort for quantifying how critical a negative patient experience is using different elements of the available textual feedback as a key basis for prioritizing interventions by service providers. This involves the identification of the different dimensions of the construct, associated linguistic markers and metrics to compute the criticality index. We also present the results of the application of our developed conceptualization to linguistic-based text analysis of a small dataset of patient experience feedback. INDEX TERMS Customer experience, construct development, linguistic analysis, intensity markers, negative event, magnitude of consequences.

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WAVELET FILTERING OF SIGNALS WITHOUT USING MODEL FUNCTIONS

Radioelectronics and Communications Systems , Sep 21, 2022

The effective wavelet filtering of real signals is impossible without determining their shape. Th... more The effective wavelet filtering of real signals is impossible without determining their shape. The shape of a real signal is related to its wavelet spectrum. For shape analysis, a continuous color wavelet spectrogram of signal level is often used. The disadvantage of continuous wavelet spectrogram is the complexity of analyzing a blurry color image. A real signal with additive noise strongly distorts the spectrogram based on continuous wavelet analysis compared to a pure signal. Therefore, the identification of a real signal by using a continuous color wavelet spectrogram is difficult. To solve this problem, for the first time, a comparative analysis of spectrograms of signals and correlation matrices is carried out. The spectrograms of signals are obtained based on continuous wavelet transformation in the form of images with areas of different colors of variable intensity. To filter the identified signal, a recursive algorithm was used, consisting of successive iterations of the filtering parameters in order to reduce the error. The study of the algorithm on groups of twenty special signals showed a decrease in the number of iterations in comparison with known methods. Correlation matrices are computed by using mathematical functions of the coefficients of discrete wavelet spectra.

Integrating AI into Customer Service: Improving the Actionability of Customer Feedback Analysis Using Machine Learning

by Nina Rizun and Anastasija Nikiforova

AIRSI2022: Technologies 4.0 in Tourism, Services and Marketing, 2022

Integrating artificial intelligence (AI) technologies into customer service is of great interest ... more Integrating artificial intelligence (AI) technologies into customer service is of great interest to firms that face a mass of feedback originating from multiple channels (Poser et al., 2022), including phone calls, emails, and social media. Particularly social media channels have increased their popularity in recent years as a notable channel of customer feedback. As such, firms require tools that can process these feedbacks at scale, including their effective prioritization. While prioritization of customer feedback has been considered from a requirements engineering perspective (Armacost et al., 1994; Haber & Fargnoli, 2019; Mastura et al., 2015; Olsson & Bosch, 2015), i.e., what features to prioritize in new product development (NPD), there has been considerably less work on prioritizing customer feedback in order to support the work of marketing and customer service. We focus on this gap.

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