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This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.

This paper aims to discuss current work and further steps of the psychological hotline launched by the National Psychological Association of Ukraine (NPA), along with a call for action to mental health professionals worldwide.

This paper describes the training and support of the NPA’s hotline staff as well as reflections on the hotline’s work from June 2022 to April 2023.

With broad international support, the NPA’s psychological hotline currently operates in 21 countries providing psychological assistance and referrals to other service providers within Ukraine and abroad. The authors propose further steps of its work, including international collaboration.

Providing citizens of Ukraine with broad public access to evidence-based remote psychological support through NPA’s hotlines is a high priority considering the war’s negative impact on mental health diverse and the limited capacity of the state mental health system.

Little is known about the gender profile of callers to crisis hotlines, despite distinct gender differences in suicide risk and behavior. The authors assessed current knowledge of the role of caller gender in the use of crisis hotlines for suicide, specifically whether there are differences in frequency, reason for call and caller outcomes by gender.

The authors conducted a scoping literature review of peer-reviewed studies published since 2000 in Medline, PubMed and PsychInfo, examining a total of 18 articles based on 16 studies.

Overall, women represent a higher percentage of calls to crisis hotlines worldwide, despite men having higher rates of suicide. Primary reasons for calling hotlines were the same for men and women, regardless of geography or culture. When gender differences in reason for call were reported, they were consistent with literature documenting gender differences in the prevalence of risk factors for suicide, including higher rates of substance use among men and higher instances of domestic violence/abuse among women.

There was variability in the studies the authors examined. This review was limited to research on crisis telephone hotlines and did not include text or chat services. Due to data reporting, the findings are constrained to reporting on a male/female gender binary.

Findings on gender differences in crisis line use suggest a need for continued research in this area to determine how to best meet the needs of callers of all genders.

Purpose: The evidence regarding the effects of the COVID-19 lockdown on domestic violence is mixed. Studies using hotline call services identify an increase on domestic violence, while studies using police reports find a decrease. One limitation is that most of these studies came from diverse regions using different types of data sources. The purpose of this study is to use two separate data sources to study this question in the same region, and to contribute to the discussion for potential mechanisms that explain this mixed evidence.

Methodology: This study estimates the effects of the COVID-19 lockdown on domestic violence in Mexico City. The authors use two separate data sources: hotline calls and official police reports. Our empirically strategy is based on a difference-in-differences methodology and an event-study design.

Findings: As a consequence of the COVID-19 lockdown, hotline calls for psychological domestic violence increase by 17%, while police reports of domestic violence decrease by 22%. To reconcile these discrepancies between hotline calls and police reports, the authors consider several potential mechanisms. The authors find suggestive evidence that the increase in psychological domestic violence is related to financial stress. Further, the results of this study indicate that the reduction in police reports is related to women facing more barriers to report their abusive intimate partners during the lockdown.

Value: These results confirm that the variation observed in the existing literature is related to the type of data being used. The mixed evidence suggests that more women suffer from psychological domestic violence as captured by hotline calls, while women encounter more barriers to report their abusive husbands to the police as captured by the official police reports.

Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.

In this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.

The complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.

The proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.

Some people regard company hotlines as an effective way of cutting organizational waste, fraud and abuse. Others hear “Big Brother” calling. Explores the evidence for each point of view.

This paper sets a case study of missing children in the Republic of Ireland against a review of international research to explore broader understandings and responses to the problem.

The study begins by reviewing the literature on pioneering American initiatives dating back to the 1970s and more recent literature from Great Britain where a series of high-profile scandals involving sexual exploitation of teenage girls provoked a number of controversial inquiries into the police and social work professions. The present study was prompted by an evaluation of the 116 000 Missing Children Hotline which was introduced to Ireland in 2012 under the auspices of the European Union (EU) Daphne III Programme by the Irish Society for the Prevention of Cruelty to Children (ISPCC).

The central conclusion emerging from analysis of the evidence is that Missing Children Hotlines remain rooted in representations of ‘stranger danger’ and disconnected from repeat runaway children who feature prominently in police reports from formal care settings or family homes and who are actively targeted by sexual predators and criminal gangs. The implications are that systemic change requires grounding in research strategies which combine police data with anthropological studies to give legitimacy to the voices of runway and sexually exploited children.

The study offers original international perspectives on missing children to epistemological research communities in the fields of social work, criminology and policing with recommendations that Missing Children and Runaway Safe-lines are targeted systemically at keeping runaway children, homeless children and at-risk-youth safe and off the streets.

The objective of this study was to analyse the influencing factors of citizens' dissatisfaction with government services during the COVID-19 pandemic to help government departments identify problems in the service process and possible countermeasures.

The authors first used cosine interesting pattern mining (CIPM) to analyse citizens' complaints in different periods of the pandemic. Second, the potential evaluation indices of customer satisfaction were extracted from the hotline business system through a hypothesis analysis and modelled using multiple regression analysis. During the index transformation and standardization process, a machine-learning algorithm of clustering and emotion analysis was adopted. Finally, the authors used the random forest algorithm to evaluate the importance of the indicators and obtain the indicators more important to citizen satisfaction.

The authors found that the complaint topic, appeal time, urgency of citizens' complaints, citizens' emotions, level of detail in the case record, and processing timeliness and efficiency significantly influenced citizens' satisfaction. When the government addresses complaints in a more standardized and efficient manner, citizens are more satisfied.

During the pandemic, government departments should be more patient with citizens, increase the speed of the case circulation and shorten the processing period of appeals. Staff should record appeals in a more standardized manner, highlighting themes and prioritizing urgent cases to appease citizens and relieve their anxiety.

The purpose of this paper is to analyze the effect of various internal controls (i.e. hotlines, regular ethics (fraud) training, surprise audits, internal and external audits and background checks) on reducing occupational fraud losses by victim organizations.

The paper, based on data from an occupational fraud report co-authored by the Association of Certified Fraud Examiners (ACFE) and Peltier-Rivest (2007), uses a multivariate regression analysis to analyze the effect of various internal controls on preventing fraud losses.

The authors’ analyses demonstrate that hotlines, regular ethics (fraud) training, surprise audits and internal audits all decrease fraud losses when used separately. However, hotlines and surprise audits are the only statistically significant controls when controlling for the potential correlation among all internal controls. Hotlines are associated with a reduction of 54 per cent in median fraud losses, while surprise audits cut median losses by 69 per cent.

This study contributes to academia and the anti-fraud profession by assessing the statistical effect of six internal controls on preventing fraud losses, while controlling for the potential correlation among these controls.

This study discusses the relative benefits (loss savings) of various internal controls to organizations, governments, managers and anti-fraud professionals. This information may help determine investment priorities in the context of scarce resources.

This paper is based on proprietary data owned by the ACFE and is the first to analyze the statistical significance of various internal controls on the reduction of fraud losses in Canada.

This study aims to conceptualize and test the effect of consumers’ perceptions of complaint handling quality (PCHQ) in both traditional and social media channels.

Study 1 systematically reviews the relevant literature and then carries out a consumer and manager survey. This approach aims to conceptualize the dimensionality of PCHQ. Study 2 tests the effect of PCHQ on key marketing outcomes. Using survey data from a German telecommunications company, the study provides an explanation for the differences in outcomes across traditional (hotline) and social media channels.

Study 1 reveals that PCHQ is best conceptualized as a five-dimensional construct with 15 facets. There are significant differences between customers and managers in terms of the importance attached to the various dimensions. The construct shows strong psychometric properties with high reliability and validity, thereby opening up opportunities to treat these facets as measurement indicators for the construct. Study 2 indicates that the effect of PCHQ on consumer loyalty and word-of-mouth (WOM) communication is stronger in social media than in traditional channels. Procedural justice and the overall quality of service solutions emerge as general dimensions of PCHQ because they are equally important in both channels. In contrast, interactional justice, distributive justice and customer effort have varying effects across the two channels.

This study contributes to the understanding of a firm’s channel selection for complaint handling in two ways. First, it evaluates and conceptualizes the PCHQ construct. Second, it compares the effects of different dimensions of PCHQ on key marketing outcomes across traditional and social media channels.

This study enables managers to understand the difference in efficacy attached to different dimensions of PCHQ. It further highlights such differences across traditional and social media service channels. For example, the effect of complaint handling on social media is of particular importance when generating WOM communication.

This study offers a comprehensive conceptualization of the PCHQ construct and reveals the general and channel contingent effects of its different dimensions on key marketing outcomes.