Attitude of Chinese public towards municipal solid waste sorting policy: A text mining study

Exploring the Chinese public's affective attitudes towards digital transformation in agriculture: A social media-based analysis

This study utilizes natural language processing techniques and panel vector autoregression methodology, to delve into the perceived attitudes of social media users towards the digital transformation of agriculture, and to assess its impact on total agricultural output and agricultural science and technology inputs. Data related to agricultural digital transformation were collected from Sina Weibo using web crawlers. The SnowNLP model was employed to infer users' attitudes, encompassing both positive and negative aspects. Furthermore, the study delves into the specific themes capturing users' positive attitudes and explores regional variations in focus. The findings reveal a sustained increase in users' interest in agricultural digital transformation since 2013. Positive attitudes primarily center around green development, agricultural intelligence, and global cooperation and innovation. Moreover, the study establishes a significant positive impact of users' positive attitudes on both total agricultural output value and agricultural science and technology investment, highlighting the constructive influence of user support on the agricultural industry's development.

Overview of municipal solid waste management in sub-tropical climatic region of North Eastern India

Municipal solid waste management (MSWM) is perceived as a global issue regardless of the place of waste generation. The amount of unmanaged waste is increasing rapidly, along with its impact on the environment and human health. In hilly areas, specifically the North Eastern Region (NER) states of India, due to the unique topography coupled with socio-economic factors, there are inadequate waste management practices marked by insufficient infrastructure, minimal research studies, and limited data availability. This paper comprehensively reviews the existing status of MSWM practices and waste treatment technologies, identifies the challenges, and discusses the prospective approaches for MSWM in NER states of India. NER, is characterized by its hilly terrain and has the most diverse demographic profile in the country. The study highlights the notable increase in waste generation in the urban population in NER. The total amount of waste generated in NER is about 2907 tons per day, with a collection rate of 86.96%, treatment at 31.09%, and landfilling at 33.67%. The biodegradable fraction makes up the majority of waste composition (more than 50%) in NER, followed by recyclables and inert. The existing MSWM consists of waste collection, transportation, and disposal with limited source segregation and treatment. All the states of NER practice open dumping and burning as the primary waste treatment and disposal system. The study discusses the challenges and prospects to ensure effective MSWM in NER. This review is a region-specific study that considers cultural diversity, topography, and socio-economic dynamics. The outcome of this review will be helpful to the researchers and policymakers in making appropriate waste management plans and improve the MSWM system in NER.

Analysis of public opinion on employment issues using a combined approach: a case study in China

To analyze the public opinion related to the employment situation, a combined approach is proposed to study the valuable ideas from social media. Firstly, the popularity of public opinion was analyzed according to the time series from a statistical point of view. Secondly, the feature extraction was carried out on the public opinion information, and the thematic analysis of the employment environment was carried out based on the Latent Dirichlet Allocation model. Thirdly, the Bert model was used to analyze the sentiment classification and trend of the employment-related public opinion data. Finally, the employment public opinion texts in different regions were studied based on the spatial sequence popularity analysis, keyword difference analysis. A case study in China is conducted to verify the effectiveness of proposed combined approach. Results shown that the popularity of employment public opinion reached the highest level in March 2022. Public opinions towards employment situation are negative. There is a specific relationship between the popularity of employment public opinion in different provinces.

Quantifying the effect of socio-economic-geo drivers on the change of municipal waste disposal in China by an integrated TWFE-PRF-SDM methodology

Municipal solid waste management and disposal in China have significantly evolved since 2000. Due to China's vast land area and significant socioeconomic and geographic disparities, nationwide waste management strategies need to be further evaluated. This study quantified the effect of social, economic, and geographic drivers on municipal waste disposal activities in 31 provincial-level administrative regions from 2003 to 2020, by establishing a methodology integrated by two-way fixed effects regression model, panel random forest, and spatial Durbin model. The results showed, in the past two decades, socio-economic-geo indicators significantly co-decided the landfill and incineration activities. In particular, the explanatory ability of GDP per capita was above 45%, while land resources and city size also showed great significance. Spatial autocorrelation analysis showed that the relationship between landfill/incineration rates and socio-economic-geo drivers changed notably from unobvious to significant with economic growth. Furthermore, the local economy and land resources displayed more impact than those of the neighboring regions, while sci-tech and education showed clear spatial spillover effects. Chinese government would carefully assess the full-scale promotion policy of incineration plants, landfill is still hold as a reasonable option for regions with specific socio-economic-geo conditions.

Explore public concerns about environmental protection on Sina Weibo: evidence from text mining

The increasingly serious problem of ecological environmental pollution warns the importance of human environmental protection behavior. However, public attention to environmental protection plays an important role in solving environmental problems. Therefore, in order to explore the environmental concerns of Chinese residents, the trends in time and space, the relationship between online retweets, and the extraction of environmental concerns, this study analyzed the data of Sina Weibo users and their comments on related posts. At the same time, we used the text mining analysis method to analyze the social media text data, and the results are as follows. In that analysis of concern about environmental protection, women show a stronger attitude and willingness to protect the environment than men, and the public in economically developed areas is more concerned. In order to further investigate the public's environmental concerns, this study also utilized the PageRank algorithm to further study the forwarding relationships between users. The study found that celebrities and some good media organizations can attract environmental attention. Finally, we use pyLDAvis technology to visualize and analyze popular environmental themes and propose reasonable countermeasures and suggestions to enhance public environmental awareness based on the research results.

A review on the effectiveness of integrated management system in institutional solid waste management in Zimbabwe

Institutional solid waste management is a critical contemporary crisis in Zimbabwe due to rapid urbanisation, disease outbreaks and population growth. Traditional approach to institutional solid waste management is almost fragmented, with various departments accountable for numerous aspects of the management process. Deficiency of coordination as well as integration among responsible stakeholders and failure to include different management strategies resulted in institutional solid waste management inefficiencies. This translates to increased environmental health problems. Therefore, this review aims to assess the effectiveness of integrated management systems in institutional solid waste management in Zimbabwe. The review was compiled using already existing literature. Institutions regarded as sources of solid waste in Zimbabwe include learning and health institutions. Barracks, prisons and police camps are part of the institutions. The institutions generate hazardous, non-hazardous, biodegradable and non-biodegradable solid waste. Solid waste from institutions is indiscriminately stored, collected and disposed through landfilling, incineration, burning, open pits and on non-designated open spaces. Most of the disposal strategies are least prioritised by the waste management hierarchy, hence have potential to cause environmental health risks. Utilisation of inappropriate management strategies is exacerbated by shortage of resources, ineffective legal framework, lack of all stakeholder participation and inadequate investment in waste reduction alternatives. Integrated institutional solid waste management is effective since it enhances involvement of all responsible stakeholders and application of various waste reduction alternatives particularly those which support circular economy. Through integrated approach, quantity of institutional solid waste disposed is limited, therefore minimising environmental health risks while maximising dumpsites lifespan.

A systematic review of the use of topic models for short text social media analysis

Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform whether the topics produced can yield meaningful insights for those examining social media data. Efforts to address this issue, including gauging the alignment between automated and human evaluation tasks, are hampered by a lack of knowledge about how researchers use topic models. Further problems could arise if researchers do not construct topic models optimally or use them in a way that exceeds the models' limitations. These scenarios threaten the validity of topic model development and the insights produced by researchers employing topic modelling as a methodology. However, there is currently a lack of information about how and why topic models are used in applied research. As such, we performed a systematic literature review of 189 articles where topic modelling was used for social media analysis to understand how and why topic models are used for social media analysis. Our results suggest that the development of topic models is not aligned with the needs of those who use them for social media analysis. We have found that researchers use topic models sub-optimally. There is a lack of methodological support for researchers to build and interpret topics. We offer a set of recommendations for topic model researchers to address these problems and bridge the gap between development and applied research on short text topic models.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10462-023-10471-x.

Exploring the restrictive factors for the development of the construction waste recycling industry in a second-tier Chinese city: a case study from Jinan

Recycling construction waste in urban cities has attracted wide attention in the government department and building industry worldwide owing to numerous benefits in economics, the environment, and society for sustainable development. Most of the research was focused on the scope of first-tier/new first-tier cities. At the same time, less attention has been paid to second-tier cities, which should be further considered because of their significant potential for increasing construction waste. Jinan is one of the pilot cities for construction waste treatment in China. This city has been chosen as the case in this study to explore critical restrictive factors for developing the construction waste recycling industry (CWRI) in second-tier cities with the adoption of combined methods of the DEMATEL-ISM-EWM. It was revealed by the results that (1) the government is the main stakeholder. In addition, the legislation, management system, incentive/support for stakeholders, and technical standards were closely associated with CWRI development in Jinan. Low landfill fees and natural ore tax rates are unique and vital restrictive factors that should receive more attention. (2) Other key restrictive factors that should be given priority were (i) the lack of green design for designers, (ii) poor classification and management of construction waste for constructors on site, (iii) tight operating funds and insufficient publicity for recycling enterprises, and (iv) insufficient research funds for research institutions. Finally, a comparison of the similarities and differences of the restrictive factors on CWRI development between second-tier and first-tier/new first-tier cities was conducted, and a series of reasonable suggestions were provided, considering the perspective of stakeholders. The research will offer a valuable reference for industry practitioners and academics interested in CWRI.

Evaluation of the household solid waste mandatory sorting policy in Shanghai: A 1-year public opinion survey

Sustainable management of household solid waste (HSW) is an essential step in realizing the development of a circular economy (CE). However, for many developing countries, HSW sorting is evolving incrementally, and focusing on the intervention role of policy and the sorting behaviour of residents can help achieve sustainable waste management. This study aims to investigate the main determinants of residents' HSW sorting behaviour and how policy particularly contributes to it. Drawing upon the theory of planned behaviour (TPB) and incorporating experiences, a conceptual framework is tested on a sample of Chinese residents in Shanghai (n = 560, from November to December 2020) using structural equation modelling analysis. The empirical results show that experience and behavioural intention greatly influence HSW sorting behaviour. Moreover, the positive attitude of residents promotes the success of HSW sorting. Subjective norms and perceived behaviour control indirectly affect behavioural intention and behaviour via attitude. The findings of this study provide policymakers with critical factors for the successful implementation of HSW sorting. We also propose policy implications to maintain and improve sorting efficiency from the perspective of residents (education, communication and publicity), neighbourhood committees (degree and efficiency of supervision) and property management companies (good infrastructure, services and processes).

External Factors Impacting Residents' Participation in Waste Sorting Using NCA and fsQCA Methods on Pilot Cities in China

Recycling waste is important as it can help to reduce environmental pollution caused by "waste siege". Source classification is an important part of the municipal solid waste (MSW) sorting process. The factors that prompt residents to participate in waste sorting have been debated by scholars in recent years; however, there are not many papers that focus on the complex relationships between them. This study reviewed the literature that concerns residents' participation in waste sorting, and it summarized the external factors that might influence residents' participation. Then, we focused on 25 pilot cities in China, and we analyzed the configuration impact of external factors on residents' participation using a necessary condition analysis (NCA) and a fuzzy-set qualitative comparative analysis (fsQCA). We found no consistency between variables, nor was there one single condition that caused residents to participate in waste sorting. There are two main methods (environment-driven and resource-driven) that can help achieve a high participation rate, and three methods that can cause a low participation rate. This study provides suggestions for the implementation of waste sorting in other cities in China, as well as developing countries, with an emphasis on the importance of public participation.

Attention and Sentiment of the Chinese Public toward a 3D Greening System Based on Sina Weibo

The rapid development of global urbanization over the years has led to a significant increase in the urban population, resulting in an imbalance in the urban green space structure. Transforming the urban 2D space green quantity into a 3D space green quantity to create 3D greenery systems (TGS) is a space resource that cannot be ignored in the process of urban green space expansion. This research gathered and analyzed Sina Weibo post information and user information related to TGS to investigate the changing trend of attention status and emotional orientation of the Chinese public on TGS. We employed web crawler technology and text mining to search and analyze the data on the Sina Weibo platform. This research aids policymakers and stakeholders in comprehending the general public's perspective on TGS and showing the transmission channel of public sentiment and the origins of negative sentiment. Results indicate that the public's attention to TGS has greatly increased since the shift in the government's idea of governance, although it still needs improvement. Despite TGS's good thermal insulation and air purification effects, 27.80% of the Chinese public has a negative attitude toward it. The public's negative sentiment of TGS housing is not solely due to pricing. The public is mainly concerned about the damage to the structure of buildings caused by TGS, the subsequent maintenance of plants, the increase in indoor mosquitoes, and lighting and humidity problems. This research helps decision makers understand the public opinion communication process via social media and provides corresponding solutions, which is of great significance for the future development of TGS.

The Supervision Mechanism of Residents' Waste Separation Behavior: Analysis Using a Tripartite Evolutionary Game Model

To promote residents' waste separation behavior, waste separation supervision has been a crucial need. This paper aims to explore the supervision mechanism of residents' waste separation behavior using a tripartite evolutionary game model. The evolutionary stability conditions of resident, property service enterprise, and the government were analyzed. The influences of the main parameters on the strategy of three stakeholders were explored through numerical simulation. The results show that the regulatory mechanism of waste separation will reach the optimal stable strategy when the following conditions are satisfied: (1) the penalty for nonclassification is higher than the difference between classification cost and the total benefit of classification; (2) the subsidy to property services enterprise is greater than the total cost of positive participation management. Residents' behaviors are mainly influenced by rewards and punishments. The behavioral strategies of property service companies are more sensitive to subsidies than penalties. In the early stage of mandatory waste separation, it is important to reduce the cost of residents' separation, develop the publics' environmental awareness, and increase the willingness of properties to participate in management. This paper presents a new perspective and theoretical guidelines for the local government and communities to supervise residents' waste separation behaviors in China and other developing countries and offers useful insights into waste separation management for other countries.

Exploration of the Dynamic Evolution of Online Public Opinion towards Waste Classification in Shanghai

Shanghai is one of the fastest-growing metropolises and the first city in China to implement mandatory waste classification. Waste classification policy of Shanghai has attracted widespread attention since its implementation in July 2019. However, previous papers have not focused on online public attitudes surrounding the implementation of a waste classification policy in Shanghai. In order to fill this gap, this paper explored the dynamic evolution of online public attitudes towards waste classification in Shanghai by using sentiment analysis technology and topic modeling technology. It was found that the proportion of negative posts each month was about 20%; therefore, online public sentiment towards waste classification in Shanghai was generally positive. Compared with the first three months of policy implementation, the public sentiment towards Shanghai's waste classification became more positive, with the exception of two special periods. Negative posts in July 2019 mainly discussed waste's environmental hazards and policy provisions. New topics in negative posts in later months focused on some specific problems, including the process of throwing away wet waste, the allocated throwing times, the number of waste cans, takeaway meal disposal, and gathering activities. Improving the factors causing the negative sentiments in the posts will help the government better implement the policy. The paper will help the government to receive higher public support for the waste classification policy in Shanghai. The present findings also have great reference significance for other cities.

How Does NIMBYism Influence Residents' Behavioral Willingness to Dispose of Waste in Centralized Collection Points?-An Empirical Study of Nanjing, China

Residents' low behavioral willingness to dispose of waste in Centralized Collection Points (CCPs) seriously hinders the operational efficiency in waste collection of CCPs regarded as NIMBY ('not in my backyard') facilities. However, fewer researchers notice NIMBY facilities with low hazards. It has been ignored that the NIMBYism may influence behavioral willingness during the operation period persistently. Meanwhile, there is no consistent conclusions on internal factors of waste behavioral willingness, which deserves further study. Therefore, this study took CCPs as a research object and aimed to investigate how NIMBYism influences residents' behavioral willingness to dispose of waste in CCPs. The extended theory of planned behavior and structural equation modeling approach involving 550 respondents were adopted to conduct the analysis. The results revealed that attitude (β = 0.295, p < 0.001), government trust (β = 0.479, p < 0.001), and perceived behavioral control (β = 0.222, p < 0.001) have statistical positive impacts on behavioral willingness to dispose of waste in CCPs. Perceived risk (β = ‒0.047, p = 0.022 < 0.05) can influence behavioral willingness negatively. Additionally, government trust (β = 0.726, p < 0.001) exerts a positive impact on attitude. Furthermore, relevant strategies were proposed to enhance residents' behavioral willingness to dispose of waste in CCPs. This study is expected to inspire the government to formulate policies from the aspects of standards and regulations, resident participation, construction, and publicity. It will provide the government instructive suggestions for the smooth operation of CCPs, and ultimately building a healthy and environment friendly society.

Topic modeling and sentiment analysis of Chinese people’s attitudes toward volunteerism amid the COVID-19 pandemic

The COVID-19 pandemic has created an urgent need for volunteers to complement overwhelmed public health systems. This study aims to explore Chinese people’s attitudes toward volunteerism amid the COVID-19 pandemic. To this end, we identify the latent topics in volunteerism-related microblogs on Weibo, the Chinese equivalent of Twitter using the topic modeling analysis via Latent Dirichlet Allocation (LDA). To further investigate the public sentiment toward the topics generated by LDA, we also conducted sentiment analysis on the sample posts using the open-source natural language processing (NLP) technique from Baidu. Through an in-depth analysis of 91,933 Weibo posts, this study captures 10 topics that are, in turn, distributed into five factors associated with volunteerism in China as motive fulfillment (n = 31,661, 34.44%), fear of COVID-19 (n = 22,597, 24.58%), individual characteristic (n = 17,688, 19.24%), government support (n = 15,482, 16.84%), and community effect (n = 4,505, 4.90%). The results show that motive fulfillment, government support, and community effect are the factors that could enhance positive attitudes toward volunteerism since the topics related to these factors report high proportions of positive emotion. Fear of COVID-19 and individual characteristic are the factors inducing negative sentiment toward volunteerism as the topics related to these factors show relatively high proportions of negative emotion. The provision of tailored strategies based on the factors could potentially enhance Chinese people’s willingness to participate in volunteer activities during the COVID-19 pandemic.

The impact of municipal solid waste sorting policy on air pollution: Evidence from Shanghai, China

Municipal solid waste (MSW) sorting not only reduces the total quantity of domestic waste but also has positive effects on urban air quality. In this study, using a careful identification strategy and air quality data at the monitoring station level in Shanghai, we estimate the causal effect of the MSW sorting policy on urban air quality. The results show that after the MSW sorting policy was implemented, the air quality index (AQI), nitrogen dioxide (NO2) and carbon monoxide (CO) decreased significantly by 2.71%, 2.07% and 3.62%, respectively. We also find a positive spillover effect from the Shanghai MSW sorting policy on the air quality of adjacent cities. The implementation of this policy has triggered changes in residents' behaviors. However, the government needs further efforts to maintain the sustainability of MSW sorting policies.

Improving Contractors' Participation of Resource Utilization in Construction and Demolition Waste through Government Incentives and Punishments

This paper develops a simulation model for analyzing how government incentives and punishments improve contractors' participation in resource utilization of construction and demolition waste (RUCDW) based on system dynamics theory. The construction industry's long-term objective is to become more sustainable and resource-effective, and as part of this objective, generated construction and demolition waste should be recycled and resource utilized. However, most contractors have little willingness to engage in RUCDW because it increases their costs. The government thus plays a vital role in improving their participation in RUCDW through a range of educational tools such as advertisements, professional training, incentives, and punishments. Among these approaches, incentives and punishments are considered the most effective because they directly change project costs. We use the Vensim software package for numerical simulation and data collected from Suzhou, China are used to demonstrate and validate the developed model. Simulation results show that the government can improve contractors' participation in RUCDW through three kinds of incentives and punishments: (1) subsidizing RUCDW; (2) increasing landfill fees; and 3) issuing fines for illegal dumping. Comprehensive application of multiple policies has a stronger effect than single policies. The established model is therefore a valuable tool for assessing the dynamic effects of government incentives and punishments on RUCDW ahead of implementation, which can provide guidance for policymakers.

Legal Early Warning of Public Crisis in Network Public Opinion Events Based on Emotional Tendency

At present, China is in the period of social transformation, and social contradictions are gradually prominent. The research on NPO (network public opinion) emergency warning methods is gradually increasing. Some existing laws and regulations are abstracted and principled in content, lacking specific implementation rules and corresponding supporting measures, especially the legal rules of emergency administrative procedures. Therefore, the legal early warning model of NPO public crisis is based on emotional dimension content, NPO emotional characteristics, emotional dimension elements, and machine learning classification algorithm to construct text ET (emotional tendencies) classifier, which can be used to make ET judgment on text data. The results show that after PSO (particle swarm optimization) algorithm optimization, the precision, recall rate, and micro-average are significantly improved, and the precision is increased by nearly 14% and 80%. The conclusion shows that using PSO optimization parameters improves the classification effect of the classifier, and a better NPO crisis early warning model can be obtained.

Understanding the Human Dimensions of Recycling and Source Separation Practices at the Household Level: An Evidence in Perak, Malaysia

Recycling and source separation (R&SS) are believed to have been the first attempt to minimise waste. This research adopted mixed methods that followed sequential quantitative then qualitative data collection, combining questionnaire surveys from 100 households, semi-structured interviews, and participatory observations to study the human dimension of waste generation and management. Scoring Assessment (with modified Bloom’s Cut Off point) indicated that households had moderate knowledge and positive attitudes yet poor behaviour, and these three components indicated no linear associations, tested using Pearson’s Correlation Coefficient. However, age group, marital status, educational level and living duration showed statistical significance with households’ participation in source separation through Chi-Square Test. Meanwhile, observation data showed that waste management mechanisms and environment had inefficiently supported households’ participation in R&SS practices (external factors: poor accessibility to services, lack of tangible incentives, and absence of restriction in consumption). Elicited data indicated that a satisfactory level of intentions, knowledge, and willingness, together with good habit and quality persuasion (internal factors), were required to drive good behaviour. Subsequently, a series of recommendations were formulated to promote gradual yet solid transformation of the waste management system, tapping on existing initiatives by considering additional parameters upon the gap in households’ knowledge, attitude, and behaviour.

The value of social media tool for monitoring and evaluating environment policy communication: a case study of the 'Zero-waste City' initiative in China

The construction of a 'zero-waste city' is a flagship policy to accelerate the development of a green, low-carbon circular economy system in China. Enhancing social participation is an important dimension to evaluate the effect of 'zero-waste city' policy construction and an effective way to promote the full achievement of correct waste classification, management, and supervision of solid waste. Based on policy communication theory, this paper aims to take advantage of social media to quantitatively measure the environment policy communication effect and provide a comprehensive panoramic measurement from dynamic characteristics and trend, communication scope, attributes of communicators, and contents dimensions. Based on post data related to 'zero-waste city' on Weibo platforms from June 2018 to November 2020, this paper innovatively constructs a measurement system of environmental policy communication that combines social media data with social network analysis and text topic analysis. Results show that from the angle of communication trend, a 'zero-waste city' public environment policy is continuously promoted on social media with an increasingly growing volume and is a subject of wide concern for the public. This study confirms the value of social media data in assessing environment policy communication effect and presents several policy implications: Government departments should strengthen environmental policy communication by using Weibo and other social media tools to improve the public's attention toward the policy and increase their participation in environmental governance; focus on people's livelihood interest in policy communication content; strengthen the interaction of the public with the content of policies by using a popular and understandable public discourse system and encourage multiple social subjects to participate in policy communication and strengthen the communication of the 'zero-waste' cultural concept.

Public expectations about the impact of COVID-19 on climate action by citizens and government

Since the onset of the COVID-19 crisis many have opinionated on how it may affect society’s response to climate change. Two key questions here are how COVID-19 is expected to influence climate action by citizens and by the government. We answer these by applying topic modelling to textual responses from a survey of Spanish citizens. The identified topics tend to be more negative than positive, and more optimistic concerning future climate action by citizens. Positive views involve increasing pro-environmental behavior and are more common among younger, higher educated and male respondents as well as among those who perceive climate change as a serious threat or positively assessed COVID-19 confinement. Negative topics express concern that financial resources for climate action will be limited due to a focus on healthcare and economic recovery. In addition, they mention government mismanagement and waste due to use of protective measures like masks and gloves as impediments to effective climate action.

Detecting latent topics and trends in blended learning using LDA topic modeling

With the rapid application of blended learning around the world, a large amount of literature has been accumulated. The analysis of the main research topics and development trends based on a large amount of literature is of great significance. To address this issue, this paper collected abstracts from 3772 eligible papers published between 2003 and 2021 from the Web of Science core collection. Through LDA topic modeling, abstract text content was analyzed, then 7 well-defined research topics were obtained. According to the topic development trends analysis results, the emphasis of topic research shifted from the initial courses about health, medicine, nursing, chemistry and mathematics to learning key elements such as learning outcomes, teacher factors, and presences. Among 7 research topics, the popularity of presences increased significantly, while formative assessment was a rare topic requiring careful intervention. The other five topics had no significant increase or decrease trends, but still accounted for a considerable proportion. Through word cloud analysis technology, the keyword characteristics of each stage and research focus changes of research were obtained. This study provides useful insights and implications for blended learning related research.

Tracing the Trends of General Construction and Demolition Waste Research Using LDA Modeling Combined With Topic Intensity

The study of construction and demolition waste (CDW) has attracted more and more attentions with the increasing CDW pollution caused by the large-scale infrastructure construction. This study used the Latent Dirichlet Allocation (LDA) combined with topic intensity to discover hot topics and development trends in the study area of CDW. First, the LDA was used for topic modeling to extract the existing topics from textual data. Second, the topic intensity was calculated for the extracted topics and the numerical values of the topic intensity represented the popularity of the topics. In this study, 4 topics were extracted from 1,849 relevant articles through the LDA modeling and topic intensity calculation. The results showed that the topic of “CDW management” had an upward trend. Topics such as “recycled aggregate,” “environmental impact,” and “study of CDW on soil” all showed a downward trend. The methods of this study can dig into the topics of CDW study and help scholars to engage in this field for better understanding the prevalence and evolution trends of these topics.

Quantitative Evaluation of Waste Separation Management Policies in the Yangtze River Delta Based on the PMC Index Model

Numerous policies have been formulated and implemented to strengthen waste separation management activities in many countries. Waste separation management policies (WSMPs) must be evaluated as the precondition for reducing deviations from policy implementation and improving waste separation performance. Based on text mining technology and the construction of a policy modeling consistency (PMC) index model, we conducted a quantitative evaluation of 22 WSMPs issued by central governmental departments and provinces in the Yangtze River Delta, China from 2013 to 2021 and analyzed their optimization paths. The results suggest that the PMC index of the selected WSMPs has an upward trend. The average PMC index of 22 WSMPs was 6.906, indicating good quality in the policy texts. The PMC index identified seven, nine, five, and one of the policies as being perfect, excellent, good, and acceptable, respectively. The characteristics of WSMPs were further illustrated through PMC surface charts. Based on this, optimization paths for WSMPs with lower PMC indexes are proposed, which indicate that existing WSMPs have great potential for optimization in terms of harsher constraint regulations, context-appropriate incentives, and cultivation of market participants. Finally, this study provides a beneficial reference for similar cities or countries to improve their performance in the management of waste separation and environmental protection.

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, we propose a design and research method of a short text mining tool based on the K-means clustering algorithm and Kano mode. An improved short text clustering algorithm is used to extract the design elements of laptops. Based on the traditional questionnaire, we extract the user’s attention factors, score the emotional tendency, and analyze the user’s needs based on the Kano model. Then, we select 10 laptops, process them by the improved algorithm, cluster the evaluation words and quantify the emotional orientation matching. Based on the obtained data, we design a visual interaction logic and usability test. These prove that the proposed method is feasible and effective.

Promoting Chinese urban residents' participation in source separation and recycling

Source separation and recycling (SSR) for municipal solid waste is an important strategy for the transition to a circular economy and requires broader resident participation. How can residents' participation in SSR be promoted? Here, we consider 13 cities in Jiangsu as microcosms of China. We quantify residents' intentions to participate in SSR by distributing a validated questionnaire to 2,963 urban residents, analyze the results through structural equation modeling, and propose localized policy recommendations. We find that residents have positive attitudes toward SSR, although 92.6% of residents in southern Jiangsu were more willing to participate than those in northern Jiangsu (84.6%). Additionally, the influencing factors and their degree of influence on resident SSR participation intentions exhibit disparities across cities. "Accessibility of SSR facilities" simultaneously affects the 13 studied cities and is a key factor. "Environmental knowledge" and "environmental attitudes" are important impact factors, with occurrence frequencies of 84.6% and 69.2%, respectively. However, laws and regulations have no significant effect on residents' SSR participation intentions. We recommend that the government create favorable external conditions related to facilities and services, promote extensive publicity and educational activities through various channels, and improve the effectiveness of SSR laws and regulations. Future SSR management strategies should be localized, flexible and comprehensive. This research could help decision makers in China and other countries design policy guides to promote SSR and help link current research areas to social development.

The influence mechanism of household waste separation behavior among college students in the post COVID-19 pandemic period

College students are one of the most important groups of participants and promoters of household waste separation. Taking Ningbo as a case study, an online + offline questionnaire survey among more than 1700 students in 10 colleges is conducted to identify the main factors and pathways influencing waste separation behavior in the post COVID-19 pandemic period. The results show that the KMO statistic is 0.926, Bartlet test is p < 0.001, indicating that questionnaire sample data is suitable for factor analysis. The modified Structural Equation Model test indicates that waste separation behavior of college students mainly results from the combined effect of eight subjective intrinsic factors and seven external situational factors. Among them, the convenience of recycling facilities, the convenience of sorting facilities and the publicity and education of sorting knowledge are the top three factors with the most significant influence. The mean value of epidemic impact factors is 0.277, which is slightly lower than conventional influence factors (0.289). Environmental Norms and Constraints are an essential component in the analysis framework of college students' waste separation behavior. In the future, society and colleges should give full play to the positive influence of the epidemic factor on college students' waste separation behavior.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10163-022-01363-3.

Analysis of agricultural exports based on deep learning and text mining

Agricultural exports are an important source of economic profit for many countries. Accurate predictions of a country's agricultural exports month on month are key to understanding a country's domestic use and export figures and facilitate advance planning of export, import, and domestic use figures and the resulting necessary adjustments of production and marketing. This study proposes a novel method for predicting the rise and fall of agricultural exports, called agricultural exports time series-long short-term memory (AETS-LSTM). The method applies Jieba word segmentation and Word2Vec to train word vectors and uses TF-IDF and word cloud to learn news-related keywords and finally obtain keyword vectors. This research explores whether the purchasing managers' index (PMI) of each industry can effectively use the AETS-LSTM model to predict the rise and fall of agricultural exports. Research results show that the inclusion of keyword vectors in the PMI values of the finance and insurance industries has a relative impact on the prediction of the rise and fall of agricultural exports, which can improve the prediction accuracy for the rise and fall of agricultural exports by 82.61%. The proposed method achieves improved prediction ability for the chemical/biological/medical, transportation equipment, wholesale, finance and insurance, food and textiles, basic materials, education/professional, science/technical, information/communications/broadcasting, transportation and storage, retail, and electrical and machinery equipment categories, while its performance for the electrical and optical categories shows improved prediction by combining keyword vectors, and its accuracy for the accommodation and food service, and construction and real estate industries remained unchanged. Therefore, the proposed method offers improved prediction capacity for agricultural exports month on month, allowing agribusiness operators and policy makers to evaluate and adjust domestic and foreign production and sales.

Risk sharing for PPP project in construction waste recycling industry in China

With the deepening urbanization, urban renewal, and reconstruction movement in China, a large amount of construction waste has been generated. In order to ease the financial pressure on the government to deal with construction waste, introducing the PPP model in the construction waste recycling industry has become popular. Based on the theory of system dynamics, this paper studies the risks of using the PPP model in construction waste recycling industry. First, a causal loop diagram was depicted according to the interaction of the main risk factors. Then, using the system dynamics software Vensim, a dynamic model of the risks of the PPP project was constructed. The results show the following: (1) the PPP project in the construction waste recycling industry is profitable; (2) For the PPP project in the construction waste recycling industry, the tendering risk will break out in 6~7 years, the greatest impact on tendering risk is the cooperation environment risk, where cooperation environment risk entropy is increased by 50% and tendering risk entropy is increased by 53.66%; (3) Construction risks will break out in 7~8 years. The construction cost, construction delay, and design defects have the greatest impact on construction risks, where entropy is increased by 50% and construction risk entropy is increased by 19.30%, 19.25%, and 19.08%, respectively; (4) The operational risk has not broken out in 10 years and is expected to break out in 10 to 20 years. Raw material power supply, production technology level, and operations management efficiency have the greatest impact on operational risk, where entropy is increased by 50% and operational risk entropy is increased by 21.52%, 20.84%, and 20.76%, respectively. These results can provide suggestions and references for the risk management of PPP projects in China's construction waste recycling industry.

Modeling the public attitude towards organic foods: a big data and text mining approach

This study aims to identify the topics that users post on Twitter about organic foods and to analyze the emotion-based sentiment of those tweets. The study addresses a call for an application of big data and text mining in different fields of research, as well as proposes more objective research methods in studies on food consumption. There is a growing interest in understanding consumer choices for foods which are caused by the predominant contribution of the food industry to climate change. So far, customer attitudes towards organic food have been studied mostly with self-reported methods, such as questionnaires and interviews, which have many limitations. Therefore, in the present study, we used big data and text mining techniques as more objective methods to analyze the public attitude about organic foods. A total of 43,724 Twitter posts were extracted with streaming Application Programming Interface (API). Latent Dirichlet Allocation (LDA) algorithm was applied for topic modeling. A test of topic significance was performed to evaluate the quality of the topics. Public sentiment was analyzed based on the NRC emotion lexicon by utilizing Syuzhet package. Topic modeling results showed that people discuss on variety of themes related to organic foods such as plant-based diet, saving the planet, organic farming and standardization, authenticity, and food delivery, etc. Sentiment analysis results suggest that people view organic foods positively, though there are also people who are skeptical about the claims that organic foods are natural and free from chemicals and pesticides. The study contributes to the field of consumer behavior by implementing research methods grounded in text mining and big data. The study contributes also to the advancement of research in the field of sustainable food consumption by providing a fresh perspective on public attitude toward organic foods, filling the gaps in existing literature and research.

Source separation, transportation, pretreatment, and valorization of municipal solid waste: a critical review

Waste sorting is an effective means of enhancing resource or energy recovery from municipal solid waste (MSW). Waste sorting management system is not limited to source separation, but also involves at least three stages, i.e., collection and transportation (C&T), pretreatment, and resource utilization. This review focuses on the whole process of MSW management strategy based on the waste sorting perspective. Firstly, as the sources of MSW play an essential role in the means of subsequent valorization, the factors affecting the generation of MSW and its prediction methods are introduced. Secondly, a detailed comparison of approaches to source separation across countries is presented. Constructing a top-down management system and incentivizing or constraining residents' sorting behavior from the bottom up is believed to be a practical approach to promote source separation. Then, the current state of C&T techniques and its network optimization are reviewed, facilitated by artificial intelligence (AI) and the Internet of Things technologies. Furthermore, the advances in pretreatment strategies for enhanced sorting and resource recovery are introduced briefly. Finally, appropriate methods to valorize different MSW are proposed. It is worth noting that new technologies, such as AI, show high application potential in waste management. The sharing of (intermediate) products or energy of varying processing units will inject vitality into the waste management network and achieve sustainable development.

Stakeholders' views towards plastic restriction policy in China: Based on text mining of media text

With the massive use of plastic products, plastic pollution has increasingly attracted worldwide attention. To deal with the problem of plastic pollution, the Chinese government issued the "Opinions on Further Strengthening the Control of Plastic Pollution" (Abbreviated as OFSCPP), which is known as "plastic restriction policy" by the public, in January 2020. It stipulates the timetable and main tasks for restricting the production, sales, and use of certain plastic products, such as plastic bags, disposable straws and agricultural mulch. Since the policy was officially implemented on January 1, 2021, people's lives in China have been considerably affected, and it has also attracted widespread attention from news media. In this study, 310 pieces of news items and information about the OFSCPP published in the first quarter of 2021 from the Baidu News website from which 44, 94, 90, 26, and 49 statements from producers, retailers, consumers, managers, and experts were extracted. The extracted words and expressions were then analyzed using the Latent Dirichlet Allocation topic model. Text analysis results showed that the production efficiency of plastic substitutes in China cannot meet market demand, consumers' experience on plastic substitutes is poor, and recycling and disposal processing information is opaque. To achieve the policy goals, the government should encourage the innovation of high-quality and inexpensive plastic alternatives, the national standards for plastic substitutes should be urgently improved, consumers' concept of green consumption should be gradually cultivated, and terminal recycling and disposal should be promoted.

The impact of informational, social, convenience and financial tools on waste sorting behavior: Assumptions and reflections of the real situation

Waste sorting behavior is an important factor in reducing raw material usage through recycling programs and seeking circular economy implementation. Despite huge efforts to promote sorting behavior, in Lithuania 6 percent do not sort waste at all. The main tools which can promote this behavior are informational, social, convenience and financial. However, to the best of our knowledge, no research has analyzed the impact of all these tools on sorting behavior: this analysis revealed which tools were the most effective and to which policymakers should pay the most attention. Furthermore, we analyzed whether the identified tools really contribute to waste sorting behavior, including statements about the current situation in the model. Therefore, the aim of this paper was to investigate the impact of informational, social, convenience and financial tools - and the real situation - on waste sorting behavior. Referring to a representative survey conducted in Lithuania, the results showed that, according to respondents, only informational and financial tools had significant impact on waste sorting behavior, which was insignificantly affected by social and convenience tools. Considering the real situation, the current situation of convenience and social tools significantly influenced waste sorting behavior. Meanwhile, the current level of the informational aspect negatively and insignificantly determined waste sorting behavior. Therefore, this study provided practical insights for policymakers into which tools contribute to waste sorting behavior, and how to promote it effectively.

The nine development bands: A conceptual framework and global theory for waste and development

Solid waste management (SWM) is an essential utility service. More than two to three billion people worldwide still lack basic services, whereas some countries are already moving beyond SWM towards waste and resource management (WaRM) and a circular economy. This paper sets out a novel conceptual framework and global theory of waste and development, providing a road map, allowing a country or city to locate their current position and plot their way ahead. We identify nine development bands (9DBs) with significant commonalities in terms of critical challenges and developmental pressure points. DB1-DB4 reflect stepwise improvement towards the new baseline of meeting the SDG 11.6.1 indicators of universal collection and management in controlled facilities (DB5). Countries can then choose to move towards environmentally sound management and the 'reduce, reuse, recycle' (3Rs) (DB6-9), with an ultimate aspiration of 'zero waste'. We test the 9DBs conceptual framework against historical journeys of higher income countries. The main application will be in low- and middle-income countries striving towards SDG 11.6.1, where it fills a key gap in the practitioners' toolkit by enabling initial framing/scoping of the problem and smarter interventions to be designed and sense checked. Key insights include targeted governance/institutional reforms, appropriate and affordable systems/technology and adapting solutions to a diversity of local needs and realities.

Environmental management strategy in response to COVID-19 in China: Based on text mining of government open information

Coronavirus disease 2019 (COVID-19) is a global pandemic and a major health emergency. In the process of fighting against COVID-19, the China Ministry of Ecology and Environment (MEE) responded quickly and set up a working group as soon as possible. This article uses text mining to retrospectively analyze the government's public information on the website of MEE during the epidemic, sort out the timeline of MEE's response to COVID-19. We find that MEE's work during the COVID-19 pandemic is focused on medical waste and wastewater treatment, environment emergency monitoring, pollution prevention, and other environmental management for supporting economic recovery. It drafted three main medical waste management plans, an emergency environmental monitoring plan, and formulated "two lists" - a Positive checklist for Environmental impact assessment (EIA) approval and a positive checklist for supervision and enforcement, to promote the resumption of work and production. 2020 is the final year of China's "three years of fighting pollution prevention and control". In the case of the sudden COVID-19 epidemic, the Chinese environment department has ensured that the quality of the ecological environment has not been affected by the epidemic prevention and control while ensuring the smooth progress of the fight against pollution. China's medical waste disposal capacity has also been greatly improved during this epidemic. The review of China's environmental management strategy in response to COVID-19 can provide a reference for countries in the world that are still in the critical period of epidemic control; it can provide action guidelines for the ecological environment system to respond to sudden pandemic events in the future.

Does Environmental Policy Help Green Industry? Evidence from China's Promotion of Municipal Solid Waste Sorting

As municipal solid waste severely threatens human health and the ecological environment, since 2019, China has started to fully practice MSW sorting in all prefecture-level cities. In this paper, we apply the event study and difference-in-difference methods to investigate how China’s green policy of promoting MSW sorting influences listed waste sorting companies from the perspective of investors’ short-term and long-term reactions. This paper finds that investors are not sensitive to the introduction of MSW sorting in the short term, the new environmental policy does not relieve the financing constraints of related enterprises in the long run, and the financing constraints of private enterprises are stricter than those of state-owned enterprises. These findings indicate that China’s current encouragement of garbage sorting is not efficient enough as it has not brought benefits to the waste classification industry yet. More measures need to be taken to eliminate uncertainties in urban waste sorting. Our paper enriches the research on China’s waste sorting practices and provides new evidence of the effects of environmental policy on related firms from the perspective of green industry.