A Novel Model for E-Business and E-Government Processes on Social Media

Stoica, Eduard Alexandru; Pitic, Antoniu Gabriel; Mihăescu, Liviu

doi:10.1016/s2212-5671(13)00200-1

Cited by 13 publications

(6 citation statements)

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“…• the use of social media in the government has changed the orientation of public policymaking (Grubmüller et al, 2013) and public policy formulation (Charalabidis and Loukis, 2012;Ferro et al, 2013b); • the use of social media in the government has re-shaped government-citizen relations, such as increasing government-citizen interactivity (Chun et al, 2010; Abdelsalam et al (2013), Chun and Luna (2012), Khan et al (2014), Kuzma (2010), Snead (2013), Zheng (2013) Local government Bonsón et al (2012), Mossbergers et al (2013) Hong, 2013;Mossbergers et al, 2013) and collaboration (Panagiotopoulos et al, 2014); and • the use of social media in e-government has brought new e-government processes (Stoica et al, 2013), risk to e-government (Joseph, 2012) and variation in municipal websites (Dolson and Young, 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

Assimilation of social media in local government: an examination of key drivers

Zhang

Xiao

2017

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Purpose The government has included social media technology applications in the public sector as part of the fifth wave of information and communications technology adoption. Academic interest in social media in the government sector has been increasing. But there has been little empirical research on the assimilation of social media in the local government. To fill this gap, based on technology–organization–environment (TOE) framework, this study aims to investigate the key technological, organizational and environmental factors that affect the assimilation of social media in local government agencies. Design/methodology/approach To empirically test the model, a survey study was conducted. Data were collected from 150 government employees in the government department of X municipal government in China. The collected data were analysed quantitatively to answer five hypotheses using structural equation model. Findings The findings suggest that technology competence, top management support, perceived benefits and citizen readiness significantly influence assimilation of social media in local government agencies. Top management support is the strongest predictor of social media assimilation in a government agency. Originality/value This study is one of the first attempts that adopted the TOE framework to understand assimilation of social media in the local government. In addition, the effect of the four factors that include one technological factor, two organizational factors and one environmental factor, namely, technology competence, top management support, perceived benefits and citizen readiness, on intention to assimilate social media was investigated.

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Section: Literature Reviewmentioning

confidence: 99%

Assimilation of social media in local government: an examination of key drivers

Zhang

Xiao

2017

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“…Third, governance of digitalized ecosystem is required. Enabling regulatory frameworks is essential to secure the effective implementation of the intended path to digitalized country's ecosystem (Stoica et al 2013). The Republic of Belarus and the Russian Federation, which adopted regulatory legal acts regulating aspects of the implementation of digital economy model, took the first steps in 2018.…”

Section: Discussionmentioning

confidence: 99%

Digital economy in Belarus and Russia: leading underpins of a new reality

Klimuk¹,

Tarasova²

2019

Proceedings of the 3rd International Conference On Social, Economic, and Academic Leadership (ICSEAL 2019)

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Many countries around the world have committed to developing national frameworks in order to regulate digital economy. The latter is often regarded as an impetus for the recovery of the world economies. Having undergone some changes and finally managed to use the full potential of the knowledge-based economy such countries as Belarus and Russian Federation are now striving to derive benefits from digital economy by adapting strategy and various guidelines for better use of information and communication technologies (ICT). However, governmental acts, decrees or whatsoever cannot guarantee hundred percent success. The transition to a new model will be much dependent on people' mindsets and attitudes to innovations. Though the changeover to digitalized ecosystem is an obvious and indisputable reality, the paths that each country choses may be quite long and winding. This paper focuses on the grasping of the concept of digital economy and its constituent components which are, in fact, crucial elements leading to either success or failure in implementing legal regulations. We also describe the current state and possible development trends of digitalized ecosystems in both Belarus and Russian Federation. 2 What constitutes digital economy? While exploring the process of digitalization of the economy it looks crucial to start with clarifying the notion itself. In a broader sense, 'digitalization' implies a socioeconomic shift initiated by the wide influx

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“…Social media analytics aims to collect, monitor, analyze, summarize and visualize social media data, and it is usually driven by specific requirements from a target application [31]. In recent years, social media analytics have been applied to politics [32][33][34], the economy [35][36], culture [37][38], the natural environment [39], health, and so on [40]. Commonly used social media analysis methods include topic modeling, semantic analysis, text classification, and sentiment analysis.…”

Section: Social Media Analytical Methodsmentioning

confidence: 99%

A WeChat Official Account Reading Quantity Prediction Model Based on Text and Image Feature Extraction

Bai

2022

IEEE Access

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This paper describes a study that built a neural network prediction model based on feature extraction, focusing on text analysis and image analysis of WeChat official accounts reading quantity. Based on the embedding method of the deep learning model, we extracted the text features in the title and the image features in the cover picture, explored the relationship between these features and the reading quantity, and built a neural network model based on these features to predict the reading quantity. The results show that there is a phenomenon of sentiment fusion in the text, and a sentence vector model based on Doc2Vec and a neural network model both had a good performance. This paper proposes a tool that can predict the reading quantity in advance and help administrators adjust the titles and images according to the predicted results. INDEX TERMSFeature extraction; neural network; WeChat official accounts; Doc2Vec; user engagement I. INTRODUCTIONSocial media platforms, such as Twitter and Facebook, provide opportunities for people to create, communicate, and share ideas. In China, WeChat is a social media platform with strong communication and influencing characteristics. Administrators apply for WeChat official accounts to publish different kinds of articles or news on the platform, and readers can obtain and share information. By November 2017, WeChat had gathered more than 10 million official accounts, including 3.5 million monthly active official accounts and 797 million monthly active users [1]. Many authors have formed their own brands through original articles and become entrepreneurs on WeChat.Previous research on WeChat has focused on user behaviors and attitudes as well as the influence mechanism and communication power of WeChat as a social media platform. Specifically, it involves user satisfaction, user attitude, user intention [2-5], user engagement behavior [6][7], and the influence mechanism and effect of WeChat as an information communication platform on service provided by users [8][9][10][11]. However, there has been little research on deeper mining and exploration of the text through natural language processing (NLP). Moreover, as far as we know, there has been little research on the analysis of the cover image of WeChat official accounts. Our study focuses on text analysis and image analysis of WeChat official accounts reading quantity, which contributes to the research in this specific field and addresses

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A Novel Model for E-Business and E-Government Processes on Social Media

Cited by 13 publications

References 3 publications

Assimilation of social media in local government: an examination of key drivers

Assimilation of social media in local government: an examination of key drivers

Digital economy in Belarus and Russia: leading underpins of a new reality

A WeChat Official Account Reading Quantity Prediction Model Based on Text and Image Feature Extraction

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