Evaluating Chinese government WeChat official accounts in public service delivery: A user-centered approach

Jiang, Tingting; Wang, Ying; Lin, Tianqianjin; Shangguan, Lina

doi:10.1016/j.giq.2020.101548

Cited by 30 publications

(16 citation statements)

References 48 publications

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“…In addition, there are two main types of sports organizations that exist in society: administrative and public service. From the experience of community sports construction in developed countries, the funding for community sports mainly comes from government input, but families, enterprises, lotteries, and other channels are also gradually becoming important sources [11][12][13][14].…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm

Dang

Liu

et al. 2021

Computational Intelligence and Neuroscience

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In this paper, a deep confidence neural network algorithm is used to design and deeply analyze the risk warning model for stadium operation. Many factors, such as video shooting angle, background brightness, diversity of features, and the relationship between human behaviors, make feature attribute-based behavior detection a focus of researchers’ attention. To address these factors, researchers have proposed a method to extract human behavior skeleton and optical flow feature information from videos. The key of the deep confidence neural network-based recognition method is the extraction of the human skeleton, which extracts the skeleton sequence of human behavior from a surveillance video, where each frame of the skeleton contains 18 joints of the human skeleton and the confidence value estimated for each frame of the skeleton, and builds a deep confidence neural network model to classify the dangerous behavior based on the obtained skeleton feature information combined with the time vector in the skeleton sequence and determine the danger level of the behavior by setting the corresponding threshold value. The deep confidence neural network uses different feature information compared with the spatiotemporal graph convolutional network. The deep confidence neural network establishes the deep confidence neural network model based on the human optical flow information, combined with the temporal relational inference of video frames. The key of the temporal relationship network-based recognition method is to extract some frames from the video in an orderly or random way into the temporal relationship network. In this paper, we use several methods for comparison experiments, and the results show that the recognition method based on skeleton and optical flow features is significantly better than the algorithm of manual feature extraction.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm

Dang

Liu

et al. 2021

Computational Intelligence and Neuroscience

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“…Additionally, the government plays an important role in improving public education through the use of SMASs. For instance, unreliable SMAS-based content is considered a potential risk, while government information published through SMAS receives public trust (Jiang et al 2021). The involvement of the government helps reduce problematic activities in IAS management such as the use of non-registered insecticides for S. frugiperda control (Kumela et al 2018); managing IAS is a labor-and cost-intensive task, which is challenged by a lack of longterm performance (Zhang et al 2019).…”

Section: Discussion and Suggestionsmentioning

confidence: 99%

Social media improves farmers knowledge of invasive alien species

Chen

Peng

Zhang

et al. 2022

Preprint

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Management of biological invasions is a tremendous challenge for both ecological and socioeconomic systems. Public education positively affects stakeholder knowledge and facilitate management of invasive alien species (IAS). However, our knowledge of the role of social media in public knowledge of IAS is elusive for the majority of invaders. In this study, we used Spodoptera frugiperda (Lepidoptera; noctuidae), one of the most notorious invasive insects in China, as a case to test the hypothesis that social media could improve farmers’ knowledge of IAS. We conducted household questionnaires at the village level in the China-Myanmar-Laos border region (China) and used quantitative descriptions and binary logistic regressions in statistical analyses. Our results indicated that farmers often used 12 social media applications on smartphones (SMASs) and obtained information about S. frugiperda from six SMASs, with high preferences for WeChat and TikTok, and obtained a high level of knowledge of S. frugiperda from SMASs; further, socio-demographic factors and of SMAS-based information significantly influenced farmers’ knowledge of S. frugiperda. We suggested that well-designed and conducted educational programs based on the use of SMASs could improve the performance of IAS management, and the government plays an important role in such a circumstance. Our findings contribute to theoretical insights into the role of public education in IAS improvement, and empirical bases for the optimization of IAS management.

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“…Alternatively, most studies on social media use in the Chinese government mainly discuss how they adopt social media for self-promotion to respond to Chinese citizens participating in public affairs (Zheng, 2013;Zheng & Zheng, 2014), or discuss interactions between government and citizens (Wang & Luo, 2019), or discuss how social media delivery digital public services and evaluate social media in public service delivery (Jiang, 2021). These researchers mainly focus on only one type of China domestic social media, such as Weibo, WeChat, TikTok.…”

Section: Literature Reviewmentioning

confidence: 99%

The Asian Conference on Media, Communication and Film 2022: Official Conference Proceedings

2022

MediAsia Official Conference Proceedings

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Histories of kamishibai (paper theater) typically trace its roots to early magic lantern shows, but Iwamoto Kenji questions this development: "At a time when many different audiovisual technologies were tied in some way to modern scientific instruments, kamishibai was made of just pictures and narrative and seemed to be a throwback to Edo-period spectacles" (2002). Iwamoto's dismissal of kamishibai as a "throwback" exposes the limitations of examining any medium in isolation rather than viewing it within an interconnected media ecology. Lyons and Plunkett argue, "In contemporary media practice, 'convergence' stands for the dominance of fusion and transferability between different forms…we are in an era in which media are always used in relation to each other" (2007). While acknowledging that the scale and interconnectedness of new media may be unprecedented, this paper asks whether theories of convergence in media ecologies may also provide new opportunities to reassess older media formats. Through a historical mapping of the transnationally shifting ecologies of magic lanterns and kamishibai through a series of omocha-e (toy-prints) from the Cotsen Children's Library collection (Princeton University Library), this paper demonstrates that kamishibai not only converged with magic-lantern technology through the mediation of omocha-e, but also that the two audio-visual media-kamishibai and magic lanternscontinued to develop in relation to each other, as they moved in tandem over time. The imaginative leap that transferred cinematic animation techniques to paper offers insights into kamishibai's resilience as a medium and its growing popularity around the world today.

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Evaluating Chinese government WeChat official accounts in public service delivery: A user-centered approach

Cited by 30 publications

References 48 publications

[Retracted] Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm

[Retracted] Analysis of Stadium Operation Risk Warning Model Based on Deep Confidence Neural Network Algorithm

Social media improves farmers knowledge of invasive alien species

The Asian Conference on Media, Communication and Film 2022: Official Conference Proceedings

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