Environmental Sustainability assessment 2.0: The value of social media data for determining the emotional responses of people to river pollution—A case study of Weibo (Chinese Twitter)

Shan, Shiguang; Peng, Jing; Wei, Yigang

doi:10.1016/j.seps.2020.100868

Cited by 35 publications

(13 citation statements)

References 21 publications

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“…Although big data may have problems of noise and low-value density, social media data, through cleaning and selection, can compensate for the poor timeliness and low coverage of traditional data and effectively support various applications. For example, in terms of social economy, studies have validated the reactions of netizens to stock trends [18], and sentiments expressed on Weibo can be used to predict the performance of stocks [19] and to analysis -disaster loss [20,21]. In the realm of public affairs, some scholars have attempted to use Twitter data to monitor epidemic diseases in real-time and to study disease transmission routes through complex networks [16].…”

Section: Introductionmentioning

confidence: 99%

Effects of PM2.5 on People’s Emotion: A Case Study of Weibo (Chinese Twitter) in Beijing

Shan

Wei

et al. 2021

IJERPH

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PM2.5 not only harms physical health but also has negative impacts on the public’s wellbeing and cognitive and behavioral patterns. However, traditional air quality assessments may fail to provide comprehensive, real-time monitoring of air quality because of the sparse distribution of air quality monitoring stations. Overcoming some key limitations of traditional surface monitoring data, Web-based social media platforms, such as Twitter, Weibo, and Facebook, provide a promising tool and novel perspective for environmental monitoring, prediction, and evaluation. This study aims to investigate the relationship between PM2.5 levels and people’s emotional intensity by observing social media postings. This study defines the “emotional intensity” indicator, which is measured by the number of negative posts on Weibo, based on Weibo data related to haze from 2016 and 2017. This study estimates sentiment polarity using a recurrent neural networks model based on LSTM (Long Short-Term Memory) and verifies the correlation between high PM2.5 levels and negative posts on Weibo using a Pearson correlation coefficient and multiple linear regression model. This study makes the following observations: (1) Taking the two-year data as an example, this study recorded the significant influence of PM2.5 levels on netizens’ posting behavior. (2) Air quality, meteorological factors, the seasons, and other factors have a strong influence on netizens’ emotional intensity. (3) From a quantitative viewpoint, the level of PM2.5 varies by 1 unit, and the number of negative Weibo posts fluctuates by 1.0168 units. Thus, it can be concluded that netizens’ emotional intensity is significantly positively affected by levels of PM2.5. The high correlation between PM2.5 levels and emotional intensity and the sensitivity of social media data shows that social media data can be used to provide a new perspective on the assessment of air quality.

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Section: Introductionmentioning

confidence: 99%

Effects of PM2.5 on People’s Emotion: A Case Study of Weibo (Chinese Twitter) in Beijing

Shan

Wei

et al. 2021

IJERPH

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“…Social value reflects a kind of social status and social contribution (Tian et al, 2011). Emotional value is the emotional belonging of a person to an activity, which can arouse people's enthusiasm in sustainable consumption behavior (Shan et al, 2021). Functional value is the consideration of product practicability in the process of sustainable consumption, and it is the most basic and original power when people buy products (King, 2016).…”

Section: Perspectives Of Scb Referencesmentioning

confidence: 99%

Reconceptualizing and modeling sustainable consumption behavior: A synthesis of qualitative evidence from online education industry

Jiang

2021

Innovative Marketing

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In recent years, the concept of sustainable consumption behavior (SCB) is largely introduced and changed continuously to be discussed with industries such as energy sector, agriculture, transportation, sharing economy, and tourism. However, the study of sustainable consumption behavior in the online education industry (SCBOEI) remains a research gap. Thus, this paper aims to identify the significance of sustainable consumption behavior and theoretically conceptualize SCBOEI. This study employs content and text analysis to reconceptualize the major theories that contribute to the research of SCB. The findings in this study show that SCBOEI is contributed of great significance to promote sustainable development. In addition, this study introduces a model of SCBOEI, in which the consumer value theory, social exchange theory, and planned behavior theory are integrated. Additionally, this paper suggests that value, environmental attitude, identity, consumer engagement, and contextual factors (government behavior, market conditions, and environmental education) are highly important to extend the research on SCBOEI. In conclusion, this study strongly recommends that SCB research shall be directed to the online education industry. Furthermore, future studies shall emphasize the empirical effects of psychological factors, activity factors, and contextual factors for SCBOEI to find the correlation.

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“…Although there are some studies on Twitter in the public sector, the literature on Twitter in local governments is rather scarce (Anderson et al, 2015;Criado & Villodre,2018;Sobaci&Karkin,2013)andalmostnon-existentintheuseofTwitter on environmental issues (Hodges & Stocking, 2016;Shan et al, 2020). A study by Wukich and Steinberg (2013) analysed how the use of hashtags facilitates the disseminationofinformationduringextremeevents.Haro-de-Rosarioetal.…”

Section: Twitter As a Tool For Environmental Disclosure In The Public Sectormentioning

confidence: 99%

Environmental Disclosure as a Tool for Public Sector Legitimacy

Ponte

Perea

Bednárová

2020

International Journal of Public Administration in the Digital Age

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The purpose of this study is to measure the extent of Twitter environmental reporting by Andalusian municipalities (Spain) and identify the determinant factors of such a disclosure. Thus, factors such as population, geolocation, political signs, and sustainable commitments were analyzed under the legitimacy theory approach. The sample consisted of the official Twitter accounts of the 153 biggest local governments in Andalusia. The classification of the environmental tweets was based on a dictionary based on the GRI reporting standards for environmental disclosure, and a Twitter environmental disclosure index (TEDI) was developed. The results show that most of the local governments in Andalusia (77.78%) have an official Twitter account with different levels of audience, penetration, and activity. On the other hand, it was found that environmental disclosure is very low. However, municipalities with more surplus budget and municipalities with a greater number of sustainable commitments networks tend to report more on environmental issues through Twitter.

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Environmental Sustainability assessment 2.0: The value of social media data for determining the emotional responses of people to river pollution—A case study of Weibo (Chinese Twitter)

Cited by 35 publications

References 21 publications

Effects of PM2.5 on People’s Emotion: A Case Study of Weibo (Chinese Twitter) in Beijing

Effects of PM2.5 on People’s Emotion: A Case Study of Weibo (Chinese Twitter) in Beijing

Reconceptualizing and modeling sustainable consumption behavior: A synthesis of qualitative evidence from online education industry

Environmental Disclosure as a Tool for Public Sector Legitimacy

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