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Safety-related concerns may emerge during the operation of unmanned aerial vehicles (UAVs), reported by users and developers in the form of issue reports and pull requests. To help UAV developers identify safety-related concerns, we propose SALIENT, a machine learning (ML)-enabled tool that analyzes individual sentences composing the issue reports and automatically recognizes those describing a safety-related concern. The assessment of the classification performance of the tool on the issues of popular open-source UAV-related projects demonstrates that SALIENT represents a viable solution to assist developers in timely identifying and triaging safety–critical UAV issues, outperforming baselines based on ChatGPT and Google’s Bard.

An Issue Tracking System (ITS) plays a crucial role in software development and provides valuable information for understanding issue management. In an ITS, software developers often discuss issues that are reported during software development. Recent studies analyzed such issue discussions and identified information types of issue comments that appeared in the discussions. Automatic classification of the information types can help developers understand and locate required information more easily, but existing techniques cannot provide accurate classification. In this study, we propose a more accurate technique to classify information types of issue comments. The key to increasing classification performance is employing random oversampling to deal with imbalances among training instances of different information types. With random oversampling, we trained a classifier using logistic regression with hyperparameter tuning and achieved an average 0.95 F1-score, which was much higher than 0.53 of the compared existing technique. We also considered two other key aspects of the technique to fully investigate the potential performance improvement. We expanded an existing issue comment dataset by adding 4,098 more instances, almost double the size of the dataset. We analyzed the influence of hyperparameters on classification performance and found that using values within an appropriate range is important to achieve high performance.

Stakeholders in software projects use issue trackers like JIRA or Bugzilla to capture and manage issues, including requirements, feature requests, and bugs. To ease issue navigation and structure project knowledge, stakeholders manually connect issues via links of certain types that reflect different dependencies, such as Epic-, Block-, Duplicate-, or Relate- links. Based on a large dataset of 16 JIRA repositories, we study the commonalities and differences in linking practices and link types across the repositories. We then investigate how state-of-the-art machine learning models can predict common link types. We observed significant differences across the repositories and link types, depending on how they are used and by whom. Additionally, we observed several inconsistencies, e.g., in how Duplicate links are used. We found that a transformer model trained on titles and descriptions of linked issues significantly outperforms other optimized models, achieving an encouraging average macro F1-score of 0.64 for predicting nine popular link types across all repositories (weighted F1-score of 0.73). For the specific Subtask- and Epic- links, the model achieves top F1-scores of 0.89 and 0.97, respectively. If we restrict the task to predict the mere existence of links, the average macro F1-score goes up to 0.95. In general, the shorter issue text, possibly indicating precise issues, seems to improve the prediction accuracy with a strong negative correlation of - 0.73. We found that Relate-links often get confused with the other links, which suggests that they are likely used as default links in unclear cases. Our findings particularly on the quality and heterogeinity of issue link data have implications for researching and applying issue link prediction in practice. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) are nowadays used in a variety of applications. Given the cyber-physical nature of UAVs, software defects in these systems can cause issues with safety-critical implications. An important aspect of the lifecycle of UAV software is to minimize the possibility of harming humans or damaging properties through a continuous process of hazard identification and safety risk management. Specifically, safety-related concerns typically emerge during the operation of UAV systems, reported by end-users and developers in the form of issue reports and pull requests. However, popular UAV systems daily receive tens or hundreds of reports of varying types and quality. To help developers timely identify and triage safety-critical UAV issues, we (i) experiment with automated approaches (previously used for issue classification) for detecting the safety-related matters appearing in the titles and descriptions of issues and pull requests reported in UAV platforms and (ii) propose a categorization of the main hazards and accidents discussed in such issues. Our results (i) show that shallow machine learning (ML)-based approaches can identify safety-related sentences with precision, recall, and F-measure values of about 80%; and (ii) provide a categorization and description of the relationships between safety issue hazards and accidents. [ABSTRACT FROM AUTHOR]

On GitHub, one of the most successful services for software project hosting, labels have been used to represent various information and decisions about reported issues. However, previous studies on labels were limited to simple statistics or label recommendations for issue types. In this paper, we aim to provide a better understanding of labels and their usage in software development. We particularly focus on using multiple and custom labels on issues. To analyze label usage, we collected software project data and label usage information from GitHub. We then quantitatively investigated the performance of projects with multi-label features and qualitatively investigated the categories of multi-labels, and the usage of multi-labels based on these categories. Our analysis results show that multi-labels are common in the majority of software projects and that projects using multi-label features manage their issues more effectively. In addition, our analysis results reveal different types of information represented by labels, which are related to features, development, and issues. This study finds several facts that can be used for studies on issue management and thus that help develop labeling techniques to mitigate the burden of issue management.

This paper employs techniques and algorithms from the fields of natural language processing, graph representation learning and word embeddings to assist project managers in the task of personnel selection. To do so, our approach initially represents multiple textual documents as a single graph. Then, it computes word embeddings through representation learning on graphs and performs feature selection. Finally, it builds a classification model that is able to estimate how qualified a candidate employee is to work on a given task, taking as input only the descriptions of the tasks and a list of word embeddings. Our approach differs from the existing ones in that it does not require the calculation of key performance indicators or any other form of structured data in order to operate properly. For our experiments, we retrieved data from the Jira issue tracking system of the Apache Software Foundation. The evaluation results show, in most cases, an increase of 0.43% in the accuracy of the proposed classification models when compared against a widely-adopted baseline method, while their validation loss is significantly decreased by 65.54%.

Regarding the traditional irrigation and drainage management methods in China's irrigation districts, there are problems such as complex management processes, dispersed information systems, difficulty in resource sharing, diverse data sources, and insufficient intelligent auxiliary decision-making. In order to further realize refined intelligent management decision-making on issues related to smart irrigation districts, this article uses the basic information of 28 Yellow River diversion irrigation districts in Henan Province, as well as the overall plan reports and related issue management manuals of 7 management offices of the first and second phase projects of Zhaokou Irrigation District as data sources. Collect and organize data from irrigation areas, and use these to build a knowledge graph for management of issues in irrigation areas diverted from the Yellow River. At the same time, the BERT + BiLSTM + CRF model is used to intelligently identify entities such as irrigation projects and problem events in the Zhaokou Irrigation District inspection log text, and entity alignment technology is used to match the inspection text with entities in the knowledge graph. Finally, combined with the graph retrieval function, the intelligent generation of smart irrigation district management decision-making solutions is realized. The validation of specific irrigation district examples and analysis of the evaluation indexes of relevant models demonstrate the reliability of the problem management decision-making scheme proposed in this paper. This application effectively facilitates the integration of information data in the Yellow River diversion irrigation area and enables visual management of intelligent irrigation zones, presenting a novel concept for the informationization construction of China's irrigation areas., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Shaonan Sun reports financial support and article publishing charges were provided by 10.13039/501100001809National Natural Science Foundation of China. Shaonan Sun reports a relationship with 10.13039/100018714North China University of Water Resources and Electric Power that includes: consulting or advisory, funding grants, non-financial support, and travel reimbursement. We declare that there is no conflict of interests regarding the publication of this article. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Public institutions seek to maintain their built-environment assets by allocating sizable budgets to small construction projects that renovate or expand upon existing facilities. Small building projects can encounter many issues, which must be effectively managed by the project team to avoid negative performance outcomes. Yet relatively little research has investigated issue management within small building projects. This study’s objectives were to quantify the frequency with which various issues arise during the construction phase and to identify the timing of the project team’s corresponding actions to manage each issue. The study’s dataset consisted of 881 small building projects, including 5,236 individual issues that the project teams identified, monitored, and resolved during the construction phase. Results show that the most frequently occurring issues were designer and owner related. Design errors and omissions and unforeseen concealed conditions were typically identified and resolved the earliest in the schedule, whereas contractor-related issues were typically the last to be identified and resolved. Owner scope changes and unforeseeable events required the longest monitoring periods before the resolution was reached. This study contributes to the body of knowledge by identifying the most frequent issues and the timing with which they were identified, resolved, and monitored by the project team. [ABSTRACT FROM AUTHOR]

Improving interpretation of existing guidelines and management of protocol deviation processes could increase process efficiencies and help reduce noise to support rapid identification of important protocol deviations. Towards this end, TransCelerate identified key principles to build upon and clarify the definition of a protocol deviation and developed a holistic approach to protocol deviation management. The approaches are flexible to suit a variety of indications, study designs, and investigational agents while also supporting consistent application within a study, program or organization. [ABSTRACT FROM AUTHOR]

This study examined how two opposing advocacy organizations, National Rifle Association and Moms Demand Action, legitimize issues related to gun violence. Through topic modeling and social network analysis of tweets from both organizations, this study analyzed how advocacy organizations dealing with controversial issues use communication to achieve certain types of legitimacy. With the consistent outbreak of school mass shootings, this study also explored the communication strategies employed by advocacy organizations to manage issues and enhance legitimacy to garner policy initiatives. The theoretical and practical implications of the findings were discussed. • Multi-level discursive strategies were used to achieve various aspects of legitimacy. • Advocacy organizations dealing with controversial issues often engage in discussions about moral legitimacy. • The presence of distinctive organizational values amplifies the salience of issues during issue management. • This study employs a computational method, enabling a comprehensive examination of large datasets. [ABSTRACT FROM AUTHOR]

This exploratory study investigates how executive-level and functional managers in three large organisations understand and respond to negative word-of-mouth (NWOM). The findings, based principally on analysis of 54 interviews over 3 years, show that organisations devote far more resources to the management of NWOM than they do to the promotion of positive word-of-mouth. Marketing and other customer-facing work groups play varied roles in organisational response to NWOM, which often involves complaints management and crisis management. We find that senior management, marketing, sales, advertising, PR and contact-centre staff all have different fears about NWOM and therefore respond to it in various ways. Our recommendations for better management of NWOM stress three points – leadership, organisational readiness and public relations management. [ABSTRACT FROM PUBLISHER]

Abstract Analysis of functional magnetic resonance imaging (fMRI) plays a pivotal role in uncovering an understanding of the brain. fMRI data contain both spatial volume and temporal signal information, which provide a depiction of brain activity. The analysis pipeline, however, is hampered by numerous uncertainties in many of the steps; often seen as one of the last hurdles for the domain. In this review, we categorise fMRI research into three pipeline phases: (i) image acquisition and processing; (ii) image analysis; and (iii) visualisation and human interpretation, to explore the uncertainties that arise in each phase, including the compound effects due to the inter-dependence of steps. Attempts at mitigating uncertainties rely on providing interactive visual analytics that aid users in understanding the effects of the uncertainties and adjusting their analyses. This impetus for visual analytics comes in light of considerable research investigating uncertainty throughout the pipeline. However, to the best of our knowledge, there is yet to be a comprehensive review on the importance and utility of uncertainty visual analytics (UVA) in addressing fMRI concerns, which we term fMRI-UVA. Such techniques have been broadly implemented in related biomedical fields, and its potential for fMRI has recently been explored; however, these attempts are limited in their scope and utility, primarily focussing on addressing small parts of single pipeline phases. Our comprehensive review of the fMRI uncertainties from the perspective of visual analytics addresses the three identified phases in the pipeline. We also discuss the two interrelated approaches for future research opportunities for fMRI-UVA.

Paracrisis in social media issues needs to be anticipated, identified, monitored, and managed. While PR practitioners already have to deal with this phenomenon on a daily basis, only few studies have examined paracrisis response strategies to find adequate ways of handling these reputation threats. The objective of this study is to test selected paracrisis response strategies on Facebook that have not yet been combined by other researchers and identify the most recommendable strategy. Drawing on social representation principles and the SCCT model (Coombs in Corp Reput Rev 10(3):163–176, 2007) as well as the SMCC model (Liu et al. in: Duhe (ed) New media and public relations, 2nd edn, Peter Lang, New York, 2012), four organisational response strategies—reform, humour, refuse, and refute—are examined in two within-subjects experiments, with self-imposed and external paracrisis origins, respectively. This experiment uses fictional paracrisis in fictional international IT suppliers. Differences and effects in respondents' perceptions of organisational reputation and paracrisis behavioural intentions are analysed. In both experiments, results show that a reform strategy is significantly the most recommendable, and a humorous strategy is the least recommendable for this paracrisis situation. This component of Public Relations practice and research can prevent potential real-world crises and protect organisations' reputations. Paracrises are social crises, and thus organisations should be able to adapt (accommodate) to communities by explaining the situation and exchanging information horizontally. [ABSTRACT FROM AUTHOR]

This research draws on complexity theory to provide an alternative conceptualization of issue management. We use six dynamics of complexity drawn from complex adaptive systems—equipoise, turbulence, sensitive conditions, bifurcation, attractor emergence, and symmetry breaking—to develop a metaphorical framework that describes what occurs during various periods of issue activity and what propels issues from one period of activity to another. We illustrate the framework with a case study of the pharmaceutical industry response to the HIV/AIDS pandemic in Sub-Saharan Africa. The article concludes with a discussion of the additional affordances this framework provides to extend and compliment issue life cycle models. [ABSTRACT FROM AUTHOR]

• A social media strategy proved useful in a campaign about HPV vaccination. • Heart-brain communication is effective in creating dialogues with target groups. • Community management resources are vital to restore confidence in HPV vaccination. To evaluate whether the social media strategy developed for the campaign Stop HPV – stop cervical cancer was successful at engaging target groups in communication regarding HPV vaccination. In 2009, the Human Papillomavirus (HPV) vaccine became part of the Danish childhood vaccination program to protect Danish girls from cervical cancer. In 2015, after a period of massive media coverage questioning the safety of the HPV vaccination, a rapid decline in HPV vaccination coverage was observed. An information campaign was therefore launched in May 2017 to address HPV vaccination hesitancy. 'Heart-brain communication' combined facts and emotions through varied content. Community management guidelines were worked out to ensure that there was positive dialogue. Key Point Indicators (KPI) for Engagement Rate (ER) and Click Through Rate (CTR) were chosen to uphold engagement and traffic from Facebook to the website. The KPIs were used to measure effectiveness. In January 2019, the social media campaign had reached 8,020,000 people with an average of 127 comments per post. The average ER from May 2017 to halfway through 2018 was 6.07% and the CTR was 2.09%. The content subgroup personal stories was the most effective in creating positive dialogue. One year after the launch of the campaign, the number of positive comments had increased from less than 50% to approximately 75%. A comprehensive social media strategy using 'heart-brain communication' proved useful in a campaign for HPV vaccination. The success of the social media strategy was due to meticulous planning prior to launching the campaign, the use of content subgroups, the allocation of adequate resources for community management, the empirical analysis of content, and the use of evaluation results as guidance for the production of new content. [ABSTRACT FROM AUTHOR]

Strategic public relations (PR) is an organisational management system for preemptive (proactive) and defensive (reactive) reputational communication. The organisational reputation is the stakeholders' evaluation of the pursuit and achievement of business goals in compliance with the moral and ethical expectations and constraints imposed by the organisation's stakeholders and the wider public. The article examines the reputation from a sociological perspective in the context of the strategic public relations applied in managing crises caused by external and internal organisational problems and incidents. [ABSTRACT FROM AUTHOR]

Abstract. discourse Analysis of Coverage in the Online Media Liputan6.com. Regarding to Establishment Issue of New Subsidiary PT. Jasa Layanan Operasi ( PT . JLO ). The research is about coverage analysis to see the implementatiom issue management through me-dia relations activations at online media by Jasa Marga’s Public Relations Officer. This study aims to determine the discourse analysis of coverage regarding to establishment issue of new subsidiary PT. JLO in the online media and to see how Jasa Marga’s public relations of-ficer exercises issue management through media relations activations to handle the issues. Using the discourse analysis method with Halliday model of analysis. The results showed that the discourse in the news are based on fact that really happened. News content is served with a different point of view and very objective. The Media shows its position as a netral posi-tion between two sides of subjects, objective, and reporting the truth to the public. it shows that media relations activations is not bring much influence to the emerging issues and nega-tive news in the media. The conclusion of this study is the coverage was experiencing news balance between negative tone and positive tone after PRO did the media relations activations. But does not eliminate the negative news regarding the issue of the establish-ment of a subsidiary JLO. Abstrak. artikel ini merupakan sebuah analisis wacana pemberitaan di Media Online Liputan6.com mengenai Isu Pendirian Anak Usaha Baru PT. Jasa Layanan Operasi (PT. JLO) serta melihat Implementasi Manajemen Isu Melalui Media Relations pada Media Online yang Dilakukan Oleh Humas Jasa Marga dengan. Penelitian ini bertujuan untuk menge-tahui analisis wacana dari Informasi pemberitaan mengenai isu pendirian anak usaha baru Jasa Marga, PT. Jasa Layanan Operasi (JLO) di media online Liputan6.com dan melihat bagaimana manajemen isu melalui kegiatan media relations dilakukan untuk mengatasi isu pendirian PT. Metode yang digunakan dalam penelitian ini adalah metode analisis wacana dengan model dari M.A.K. Halliday. Hasil penelitian menunjukkan bahwa wacana dalam beri-ta berisikan fakta – fakta yang benar terjadi, walaupun dengan tone yang berbeda-beda, positif-negatif-netral. Konten berita yang disajikan dari media online ini memiliki sudut pandang yang berbeda – beda dan objektif. Media menunjukkan posisinya sebagai posisi yang netral, ob-jektif, dan pelapor kebenaran kepada khalayak, sehingga menunjukkan upaya media relations yang dilakukan oleh humas Jasa Marga tidak begitu membawa pengaruh banyak terhadap berkembangnya isu dan pemberitaan negatif yang dimuat. Kesimpulan dari penelitian ini ada-lah pemberitaan mengalami keseimbangan tone antara positif dan negatif setelah dilakukannya upaya media relations, namun tidak menghilangkan pemberitaan negatif mengenai isu pendirian anak usaha JLO.

This paper analyses the requirements for managing interoperable building data in a federated Common Data Environment (CDE). We discuss the need for generic (meta)data storage patterns, semantic query interfaces, decentral authentication, data aggregation, and adaptation and prove that their combination is feasible with current-day technologies. We illustrate the mechanisms of such federated CDE by considering the topic of digital Issue Management, one of the primary functions of a CDE. In an exemplary data flow process, we show how generic (federated, Semantic Web-based) data patterns for Issue Management can be aggregated and restructured to match existing industry standards like buildingSMART's BIM Collaboration Format (BCF) API. Finally, we show the methodology is compatible with current-day practice by implementing this process in a proof of concept. The main contribution of this research is a generic, federated framework for project-related, interdisciplinary collaboration for CDEs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Social Sciences Research / Sosyal Bilimler Arastirmalari Dergisi is the property of ODU Journal of Social Sciences Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Influence over business paradigms due to changing economic, political and social environments indicates a new period in which stakeholder relationships comes to prominence in terms of organisations. Public relations are seen to be evolved into a strategic role in order to cope with the rapid change. Strategic public relations which based on adaptation to environment as an institutional entity are seen to be advanced by some concepts and approachs in teoritical and practical regards. It needs to be analyzed theoretical and practical dimentions to understand the direction of subjects of strategic public relations. It is the aim of this work to manifest the direction and frequency of the subjects within strategic public relations in international field. It will be tried to work out which subjects in which frequency are dealth with and perspective of the works in the sense of strategic public relations by researching the papers in the journals which are published in English language. The findings suggest that the topics within the strategic public relations in the journals published in English comprise one out of every four articles and these articles to a large extent support the theory of strategic public relations. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Management & Business Research (2521-4306) is the property of Chinese Management Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Our paper focuses on some of the controversies concerning the field of public affairs. Considered to be a constantly evolving discipline, public affairs encompass a large and diverse repertoire of tools and techniques, amongst which the most renowned is, by far, lobbying. Regardless of the formal definition preferred (the simplest one, quoted by Phil Harris and Craig Fleisher, is the totality of government affairs or relations), the nucleus of public affairs work concerns the process of policy formulation and its possible impact on corporations. Evidently, the latter entails the involvement of further stakeholders (individuals, interest groups, communities) that could be affected by the issue at stake. Usually, solving this issue proves to be dependent on legislative or regulatory bodies. When lobbyists influence the government and its policies, they actually produce relevant modifications of the external environment in terms of politics, economics or the justice system. Although these practices have quite a long history in many countries, scholars still strive to find appropriate theoretical frameworks in order to provide better explanations. Using an idea articulated by Rob de Lange and Paul Linders, we argue that constructionism represents a valuable option both in terms of explanatory power and in terms of anti-essentialist standpoint. [ABSTRACT FROM AUTHOR]

Many anthropologists work with corporations to understand and work effectively with communities impacted by their activities. This paper presents a Social Ecology model oriented to citizen empowerment and impact management, identifying concepts that shape ethnography into a management framework: informal networks and routines, human geography, and citizen issue management. Affecting corporate behavior can be accomplished in phases, from community assessment, to issue management, to ethnographic training programs. Their applications are described in a subdivision development, an electric utility project, and a program of paradigm change in the right-of-way, infrastructure and energy industries. [ABSTRACT FROM AUTHOR]