Public attention and sentiment of recycled water: Evidence from social media text mining in China

Li, Li; Liu, Xiaojun; Zhang, Xinyue

doi:10.1016/j.jclepro.2021.126814

Cited by 46 publications

(23 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…As mentioned above, the public attention towards the Beautiful Village Initiative has been rarely discussed; but, unsurprisingly, the phenomenon that the development or construction of the matter is uncoordinated with public attention has also been analyzed in related research fields. The public attention related to wastewater and the wastewater treatment has positive correlations to a certain extent [64]; however, the scarcity of water resources and the popularization of recycled water do not necessarily cause more public concern, and may even cause negative emotions, such as an aversion to using recycled water [65]. The scholars who study tourism have found that the construction quality and development level of scenic spots cannot completely determine the network attention, public preference, and demand [66,67].…”

Section: Discussionmentioning

confidence: 99%

Understanding Public Attention towards the Beautiful Village Initiative in China and Exploring the Influencing Factors: An Empirical Analysis Based on the Baidu Index

Yang

et al. 2021

Land

View full text Add to dashboard Cite

The implementation of China’s Beautiful Village Initiative was an extraordinary achievement and aroused extensive public attention. However, existing research mostly focuses on the construction and seldom on public attention towards the Beautiful Village Initiative. For this reason, this paper investigated the spatiotemporal characteristics of public attention based on the Baidu index using time-constrained clustering and the spatial autocorrelation test. Our results showed that the evolutionary process can be divided into three stages: very little national attention (2011–2012), injection of a strong impetus (2013–2015), and rooted in the people’s minds (2016–2020). Spatially, provincial public attention demonstrated obvious spatial differentiation and stable spatial autocorrelation, with Low–Low clusters in Northwest China and High–High Clusters in East, Central, and North China. Spatial econometric models were further utilized to quantify the effects of socioeconomic factors on public attention. The results of the SEM model proved the existence of spatial spillover effects and indicated that the urbanization rate, population density, education level, and network popularity rate all positively affected public attention. The relationship between Beautiful Village construction and public attention was uncoordinated and, in most provinces, advances in public attention were ahead of the construction level. Our findings contribute to the understanding of public attention towards the Beautiful Village Initiative, and policy suggestions we proposed would be applied to increasing public awareness and participation.

show abstract

Section: Discussionmentioning

confidence: 99%

Understanding Public Attention towards the Beautiful Village Initiative in China and Exploring the Influencing Factors: An Empirical Analysis Based on the Baidu Index

Yang

et al. 2021

Land

View full text Add to dashboard Cite

show abstract

“…Na et al (2021) improved the text mining approach for extracting the safety risk attributes from construction accident reports by proposing the information entropy weighted term for term-importance assessment and accumulating the term frequency for gathering the threshold division. The combination of text mining and web crawling is more objective and productive than the previous technique adopted in social science research for addressing unstructured datasets (Andiappan et al, 2021;Wang et al, 2019;Li et al, 2021). Accordingly, an increasing number of researchers have attempted to integrate text mining with web crawlers to analyze social media data to reduce subjective effects.…”

Section: Proposed Methodsmentioning

confidence: 99%

Reconfiguring a hierarchical supply chain model under pandemic using text mining and social media analysis

Yan

Ren

et al. 2022

IMDS

View full text Add to dashboard Cite

PurposeThis study is to reconfigure a hierarchical supply chain model utilizing databases and text files to understand future pathways due to COVID-19 pandemic has had a bullwhip effect, disrupting the global supply chain, and a mechanism is needed to address this disruptive event under pandemic uncertainties.Design/methodology/approachTo address this mechanism, this study employs bibliometric analysis and text mining to reconfigure a hierarchical supply chain model under pandemic conditions and associates it with social media to conduct an intuitive visual analysis.FindingsThe current academic concerns are related to an overconcentration on risk management and a data-driven approach, generating an enormous gap between the concerns of academics and those of the public. The evidence shows that for both countries with outstanding performance and those that need improvement, the efficiency in terms of preventing the spread of the pandemic should be promoted.Originality/valueThis study contributes to (1) reconfiguring a hierarchical supply chain model under pandemic uncertainties and (2) bridging theory and practice by offering comparable interrelated attributes to guide post-COVID-19 strategies in the supply chain. The findings are that the supply management approach and big data are attributes that involve the concerns of world public and academics under pandemic uncertainties.

show abstract

“…Weibo has been deployed as a data source by many studies focusing on issues in China (Tao and Su, 2021 ; Wu et al, 2021 ). Octopus, a mature web crawler tool, was used to collect data from Weibo, as it has shown great effectiveness in previous studies (Li et al, 2021 ; Liu and Hu, 2019 ). In addition, it should be noted that the data collection process was implemented daily to acquire the maximum amount of data.…”

Section: Methodsmentioning

confidence: 99%

Cyber violence caused by the disclosure of route information during the COVID-19 pandemic

Lian

Zhou

Lian

et al. 2022

Humanit Soc Sci Commun

View full text Add to dashboard Cite

Disclosure of patients’ travel route information by government departments has been an effective and indispensable pandemic prevention and control measure during the COVID-19 pandemic. However, this measure may make patients susceptible to cyber violence (CV). We selected 13 real cases that occurred in China during the COVID-19 pandemic for analysis. We identified several characteristics that commonly appeared due to route information, such as rumors about and moral condemnation of patients, and determined that patients who are the first locally confirmed cases of a particular wave of the pandemic are more likely to be the victims of CV. We then analyzed and compared six real cases using data mining and network analysis approaches. We found that disclosing travel route information increases the risk of exposing patients to CV, especially those who violate infection prevention regulations. In terms of disseminating information, we found that mainstream media and influential we-media play an essential role. Based on the findings, we summarized the formation mechanism of route information disclosure-caused CV and proposed three practical suggestions—namely, promote the publicity of the media field with the help of mainstream media and influential we-media, optimize the route information collection and disclosure system, and ease public anxiety about the COVID-19 pandemic. To our knowledge, this study is one of the first to focus on CV on social media during the COVID-19 pandemic. We believe that our findings can help governments better carry out pandemic prevention and control measures on a global scale.

show abstract

Public attention and sentiment of recycled water: Evidence from social media text mining in China

Cited by 46 publications

References 41 publications

Understanding Public Attention towards the Beautiful Village Initiative in China and Exploring the Influencing Factors: An Empirical Analysis Based on the Baidu Index

Understanding Public Attention towards the Beautiful Village Initiative in China and Exploring the Influencing Factors: An Empirical Analysis Based on the Baidu Index

Reconfiguring a hierarchical supply chain model under pandemic using text mining and social media analysis

Cyber violence caused by the disclosure of route information during the COVID-19 pandemic

Contact Info

Product

Resources

About