Department of Urban and Environmental Engineering (Urban Infrastructure Engineering) .. online civil complaints from text mining and their impact on crash risk. Civil complaint investigations have not been actively conducted in the field of urban planning. Previous efforts have focused on the administrative aspects of e-government or on exploring the types of civil complaints registered for specific events.
This research identifies the characteristics of the online civil complaints using the text mining technique and examines the risk complaints as risk perception data. To date, previous investigations into civilian complaints have mainly focused on complaints about the specific issues. Moreover, civil complaints, especially when it comes to accident risk and safety, can have an objective purpose.
Second, we classify the civil complaints indicating the accident risk and rank them according to dong district scale. In the first part, we examined the characteristics of civil complaints registered on Saeol system. In the second part, we examined the relationship between accident frequency and perceived accident risk, measured by civil complaints.
Analytical methods
Results
Overall of civil complaints in Seoul
Second, a great deal of emphasis is placed on housing issues related to renovation, construction and housing associations. There is also the word 'request', a lot of people seem to be asking about the administrative process for a renovation project. In relation to the risk of collision, a situation in which an accident could occur or an uncomfortable walking pattern due to improperly parked cars is described in detail.
These types of complaints mainly describe the necessity of each facility due to safety, accident risk and crime risk. In the case of street light, people mainly ask to install it because of the fear of crime risk. It is also requested because of the accident risk, and the aim is to prevent the cases where drivers cannot see the pedestrian because it is too dark.
Regarding the pavement, there are many requests for maintenance, while the main request related to crosswalk installation in a new location. Even one district specifically mentions the cost of crime detection CCTV and it is currently impossible to install due to financial reasons. Regarding the noise problem, most of the complaints are written by the residents of one particular apartment.
While groups that consider themselves animal welfare organizations, rather than residents, tend to report animal-related complaints. In addition to common items, what appears in the graph is considered group complaints and is displayed according to specific problems. Third, claims of facilities that do not have a risk of collision are also classified as claims of a risk of collision if the facilities correspond to a pedestrian crossing, traffic light and reflector.
In the case of a crosswalk, people usually request installation up to the point where they feel they have to cross. In addition, pedestrians have limited visibility of oncoming vehicles due to the cars, which can lead to a collision. The node size and text size indicate the weighted degree and the color is assigned according to the modularity class.
Third, regarding the inconvenience of walking, many residents write about the situation of walking on the roadway because of the street vendors installed on the sidewalk and request that it be demolished.
Descriptive statistics and correlation results
Although the result of an accumulation of eight years is that there is a total number of complaints about accident risk in 150 dong districts, this is zero. For the dependent variable: total number of accidents (crash), fatal accident (death), car-to-car accidents (car_car), pedestrian-car accident (pedestrian), signal violation accident (v_signal), and pedestrian protection violation accident (v_pedestrian) for used for eight years. The lowest number of crashes occurred in Suha-dong, Jung-gu, which has only two blocks.
If we therefore assume that the accident frequency is relatively proportional to the area, then the number of accidents may be underestimated considering the district area. It shows that there are large differences in the number of accidents and also in the accident risk complaints. In the case of the small area group (below 1𝑘𝑚2), the average values of collision risk complaints were 2.4 for 8 years.
Third, for vehicle exposure – road density – is negatively related to the number of accidents. Correlation results between crash risk complaints and crash and fall independent variables Correlation between crash and complaints. When population and employment exposure are taken into account, the correlation between falls and complaints drops significantly to 0.0483.
Therefore, it can be said that the high correlation figure (0.7005) between collision with collision and collision risk originates from exposure. We also performed the correlation test between crashes and complaints according to the area groups. The first group, which has the districts above 1𝑘𝑚2, shows the significant correlation between normalized accident and normalized accident risk complaints.
The results of the correlation table show that there is no significant relationship between the number of traffic accidents and the number of complaints about the risk of traffic accidents. Exposure (number of residents and employees) explains most of the correlation between traffic accidents and complaints.
NB regression model
As expected in the correlational part of the results, there is no significant relationship between accident and accident risk complaints. While exposure variables (pop + emp, pop density, emp density, children % and elderly %) explain the accident with high significance (p<0.01). As these ages are sensitive to traffic accident risk, we expected it to have a positive relationship with traffic accident, but the results show a negative effect.
For the facility variables, the crosswalk density shows the calming effect on the accident, as previously expected. In the case of school density, the same effect also appears for zebra crossing density. Among them, three types of accidents (car-car, death and v_signal) show the statistically significant results with the facility complaints.
Facility complaints, represented as the degree of perceived accident risk of people in relation to the traffic safety facilities, show positive association with three types of accidents. But the effect of job density shows the negative association with accidents, which is somewhat different with previous research. But in the neighborhood scale, it shows the negative association with the accident (Park, 2016; Ouyang, 2014).
Male % variables were not shown the meaningful relationship with the overall crash modeling, but in models 3 and 4 it shows the strong relationship with each type of crash. In terms of amenities, pedestrian density, school density, bus stop density, parking density are marginally associated with accident rate. In the case of pedestrian density, it shows the same results with fatal crash and pedestrian-car crash.
Only in the pedestrian-car accident is the ratio of residential area positively associated with accident incidence. First, the variable for collision risk complaints has a strong correlation with the number of accidents in the group under 1𝑘𝑚2.
Two-way fixed effect NB regression model
Compared to the NB model, which used the aggregate value of accidents and claims, there are some changes in the sign and significance of the variables. Second, the sign of the road density and pedestrian crossing density coefficients changes in the opposite direction compared to the NB model.
Discussion
Although the number of accident risk complaints is too low compared to the population and the number of employees, it appears that as soon as a complaint is registered, there is a great danger in that region. Districts of less than 1𝑘𝑚2 show the statistically significant relationship with the accident risk complaints in the negative binomial model. Actually, the number of accident complaints is too small compared to the number of accidents or the population and the number of employees.
Moreover, the risk complaints indicate the specific points, but this study analyzed the accident risk models on an aggregated dong scale. This is considered the reason why large differences are observed between the two district groups (area above 1𝑘𝑚2 and area below 1𝑘𝑚2). However, in the case of Seoul, people can register complaints through three channels: the Saeol system, E-people (shinmungo), and the Eungdapso homepage.
It seems that people register the complaints spread to three services because E-people and Eungdapso are reorganized in 2008 and 2014 respectively. Although we built the data as a panel form, only the breakdown and the number of complaints change with time.
Conclusion
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