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Since crude oil is crucial to the nation's economic growth, crude oil futures are closely related to many other markets. Accurate forecasting can offer investors trustworthy guidance. Numerous studies have begun to consider creating new metrics from social networks to improve forecasting models in light of their rapid development. To improve the forecasting of crude oil futures, the authors suggest an integrated model that combines investor sentiment and attention.

This study first creates investor attention variables using Baidu search indices and investor sentiment variables for medium sulfur crude oil (SC) futures by collecting comments from financial forums. The authors feed the price series into the NeuralProphet model to generate a new feature set using the output subsequences and predicted values. Next, the authors use the CatBoost model to extract additional features from the new feature set and perform multi-step predictions. Finally, the authors explain the model using Shapley additive explanations (SHAP) values and examine the direction and magnitude of each variable's influence.

The authors conduct forecasting experiments for SC futures one, two and three days in advance to evaluate the effectiveness of the proposed model. The empirical results show that the model is a reliable and effective tool for predicting, and including investor sentiment and attention variables in the model enhances its predictive power.

The data analyzed in this paper span from 2018 through 2022, and the forecast objectives only apply to futures prices for those years. If the authors alter the sample data, the experimental process must be repeated, and the outcomes will differ. Additionally, because crude oil has financial characteristics, its price is influenced by various external circumstances, including global epidemics and adjustments in political and economic policies. Future studies could consider these factors in models to forecast crude oil futures price volatility.

In conclusion, the proposed integrated model provides effective multistep forecasts for SC futures, and the findings will offer crucial practical guidance for policymakers and investors. This study also considers other relevant markets, such as stocks and exchange rates, to increase the forecast precision of the model. Furthermore, the model proposed in this paper, which combines investor factors, confirms the predictive ability of investor sentiment. Regulators can utilize these findings to improve their ability to predict market risks based on changes in investor sentiment. Future research can improve predictive effectiveness by considering the inclusion of macro events and further model optimization. Additionally, this model can be adapted to forecast other financial markets, such as stock markets and other futures products.

The authors propose a novel integrated model that considers investor factors to enhance the accuracy of crude oil futures forecasting. This method can also be applied to other financial markets to improve their forecasting efficiency.

The purpose of this paper is to examine Chinese police officers’ general support for police intervention into domestic violence, emphasizing adequate protection of the victims, and specific support for utilizing arrests to deal with the offenders.

This study relies on survey data collected from 1,064 police officers who worked in multiple areas in two provinces of China between June and July of 2019. OLS models were used to test whether organizational variables are significant predictors of officer attitudes toward domestic violence intervention.

Both agency endorsement and supervisory support are positively related to officers’ favorable attitudes toward police intervention into domestic violence and using arrests to handle offenders. The amount of training received from the agency on the recently promulgated Anti-Domestic Violence Law, however, has a negative influence on officer support for general intervention into domestic violence and no influence on officer attitudes toward arrests.

This study represents one of the first attempts to investigate the connections between organizational and managerial factors and Chinese officers’ support for both general and specific interventions into domestic violence. It contributes to the current literature that only included police cadets in the analysis of Chinese police attitudes toward domestic violence despite the fundamental differences between cadets and active-duty officers.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.

China has been going through a “museum boom” paralleling the domestic tourism boom since 2000; such growth changed the cultural landscape; museums became a vital characteristic of some Chinese cities for both residents and tourists. Encouraged by this growth, the more ambitious “All-for-one Museum (全域博物馆)” was proposed. The physical boundary between museums and living spaces is infinite ambiguity, challenging the idea of museums as “heterotopias.” This study aims to explore the musealization of urban spaces in the context of anthropology and museology, scrutinizing the cultural-political intentions and meanings of these developments, and seeks to ignite further investigation into the reconstruction of historical imaginaries for tourists and urban populations across related disciplines.

This paper examines two cases in Chinese metropolises, Beijing and Shanghai, to illustrate this development of musealization, that is, how the cities actively leverage museological values and methods to connect with their past. In the Beijing case, the authors explore how the local government is leading the effort to musealize the city; in the Shanghai case, they will see how tourists, especially dweller-tourists, navigate through a curated past story in the city and connect their own experience, memory and identity with the place.

The all-for-one museum creates a museal layer projected onto the bigger urban space, even though the authenticity of the “past” is challenged by the modernization development of the city. The authors also find out that for some tourists (especially dweller-tourists), an existential sense of authenticity plays a more significant role as they not only seek to sightsee the past of the city but also to take part in its creation.

This paper discusses two kinds of musealization in cosmopolitan cities of Beijing and Shanghai: top-down and bottom-up. It approaches questions about the musealization of urban spaces from the perspectives of anthropology and museology, and discusses musealization in the specific historical context of China’s modernization process.