Robust Complaint Processing in Portuguese

The Natural Language Processing (NLP) community has witnessed huge improvements in the last years. However, most achievements are evaluated on benchmarked curated corpora, with little attention devoted to user-generated content and less-resourced languages. Despite the fact that recent approaches target the development of multi-lingual tools and models, they still underperform in languages such as Portuguese, for which linguistic resources do not abound. This paper exposes a set of challenges encountered when dealing with a real-world complex NLP problem, based on user-generated complaint data in Portuguese. This case study meets the needs of a country-wide governmental institution responsible for food safety and economic surveillance, and its responsibilities in handling a high number of citizen complaints. Beyond looking at the problem from an exclusively academic point of view, we adopt application-level concerns when analyzing the progress obtained through different techniques, including the need to obtain explainable decision support. We discuss modeling choices and provide useful insights for researchers working on similar problems or data.

‘Everyone’s Annoyed’: Leveraging Uncertainty in the Smell of Others

A growing literature illuminates the limits of claims made on the basis of sensory perception in scientized, rationalized, and bureaucratic contexts. How to understand exceptions to the rule – cases where claims based on sensory experience are taken at face value, even without corroborating evidence? Here, I focus on one such exception, in which citizen complaints about the smell of a small shantytown functioned successfully as both demands and justifications despite a lack of the kinds of instrumentally and technologically enabled corroboration that the literature would suggest are necessary to strengthen such claims. I show how complaints slotted neatly into a specific cultural structure, an olfactory cosmology in which ‘bad air’ that endangers health can be identified by smell and requires ongoing management and amelioration, and where adherence to hygienic norms is required for full moral citizenship. The case suggests ways that the apparent weaknesses of olfactory claims might allow them to be uniquely weaponized in social and political life, and shows how such claims can exploit shared norms, values, and meanings to enroll others in the demand for action.

Spatial Analysis of Citizens’ Environmental Complaints in China: Implications in Environmental Monitoring and Governance

Citizen environmental complaints play a key role in China’s current environmental monitoring network and environmental governance system. Based on 5796 cases of environmental complaints lodged by citizens via hotline and the internet to the MEP of China, we examined the spatial characteristics and influencing factors of citizen complaints for the period of 2013–2017 using spatial analysis methods and spatial econometric models. The roles of citizen complaints in the two systems were then reevaluated. The results show that, among all cases, 75.88% of cases were identified as verified complaints, while nearly a 25% noisy rate directed large amounts of inspection resources to be utilized in response to nonverified cases. Air pollution received the most attention by citizens in China, accounting for 67.22% of total cases. The hotspots of citizen complaints were mostly distributed in the three major national urban agglomerations in China. We found that industrial wastewater and SO2 were positively associated with the likelihood of citizens filing complaints, while the effect of industrial soot/dust emission was insignificant. Citizen complaints might be triggered by certain, but not all, forms of pollutants, even though highly visible particulate pollutants did not necessarily induce corresponding complaints. Moreover, the negative relationship between citizen complaints and per capita GDP revealed the unbalanced geographical pattern between economical development and environmental quality. The proliferation of the internet greatly facilitated citizens lodging complaints through various ways. The synergy mechanism between citizen environmental complaints and other parts in China’s environmental monitoring and governance system should be established in the future.

Symbolic Representation, Expectancy Disconfirmation, and Citizen Complaints Against Police

The theory of symbolic representation expects that citizens will view the actions of government as more legitimate when administrators share their characteristics. Although there is support for this assertion in some service areas, the evidence in policing is mixed. We draw on Expectancy Disconfirmation Theory to develop the expectation that policing is an area where we may be unlikely to see a positive relationship between representation and positive citizen perceptions of government officials. We test this expectation in an individual-level analysis of citizen complaints against police from four American cities between 2014 and 2017. The results suggest that, all else equal, complaints against Black officers are as or more likely to be filed by Black citizens than by citizens of other races. We conclude with a discussion of the implications of these results for both the study of representative bureaucracy and for the management of police citizen interactions.

Procedural and distributive justice: Effects on attitudes toward body-worn cameras

The purpose of this study was twofold. First, it examined how procedural and distributive justice influence college students’ perceptions of adoption of body-worn cameras by the police. Second, it explored how procedural and distributive justice influence college students’ perceptions of the ability of body-worn cameras to improve community relations, decrease citizen complaints, increase police officer respect, increase citizen respect, and improve training. Those who perceived distributive injustice were more likely to agree that the police should adopt body-worn cameras. Perceived distributive injustice was also a consistent predictor regarding the varying abilities of body-worn cameras.

Prioritization of public services for digitalization using fuzzy Z-AHP and fuzzy Z-WASPAS

In this paper, public services are analyzed for implementations of Industry 4.0 tools to satisfy citizen expectations. To be able to prioritize public services for digitalization, fuzzy Z-AHP and fuzzy Z-WASPAS are used in the analysis. The decision criteria are determined as reduced cost, fast response, ease of accessibility, reduced service times, increase in the available information and increased quality. After obtaining criteria weights using fuzzy Z-AHP, health care services, waste disposal department, public transportation, information services, social care services, and citizen complaints resolution centers are compared using fuzzy Z-WASPAS that is proposed for the first time in this paper. Results show that health care services have dominant importance for the digitalization among public services.