Social Sciences
We propose a more challenging dataset known as Weibo23. By amalgamating all available fake news from the Weibo Management Community until March 2023 with existing samples from public datasets [1], we formed a comprehensive collection of fake news for Weibo23. Fabricated news articles were thoroughly examined and authenticated by certified experts.
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1、 The destruction of the Kakhovka hydropower Station in the conflict raised public concern that major water projects could be damaged by the war. During World War II, China's Yellow River dams were damaged by war, and floods killed countless people. Today, the Chinese are still concerned and angry about the possible devastating floods caused by the war damage. The destruction of the Kakhovka has intensified the fear.
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1、 The destruction of the Kakhovka hydropower Station in the conflict raised public concern that major water projects could be damaged by the war. During World War II, China's Yellow River dams were damaged by war, and floods killed countless people. Today, the Chinese are still concerned and angry about the possible devastating floods caused by the war damage. The destruction of the Kakhovka has intensified the fear. 2、 Water conservancy project has accompanied the progress of human civilization, while war has been a tragic and frequent occurrence throughout history.
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Carbon information disclosure has become a threshold for equity financing of listed companies in china. Therefore, it is of great significance to explore the relationship between carbon information disclosure and equity financing costs. This study analyzes the carbon disclosure and equity financing cost data of 1731 A-share listed companies in Shanghai and Shenzhen from 2013 to 2021, panel data models and instrumental variables are used. The results show that the improvement of carbon information disclosure quality significantly reduces the equity financing costs of enterprises.
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This survey dataset delves into the diverse experiences and perspectives of individuals, focusing on key aspects of their educational journey and subsequent career choices. Comprising more than 60 questions or attributes,respondents were asked to share insights into their personal background, educational history, university preferences, and current professional status. The questionnaire covers a range of topics, including high school experiences, university decision-making criteria, major selection influences, and post-graduation outcomes.
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Compared with traditional finance, digital finance introduces digital technology for financial innovation, which largely reduces financial exclusion and discrimination, but improved financial services, such as mobile payment, online lending, virtual currency, and investment and wealth management, also involve potential risks. Hence, we propose a sentiment analysis model, GABP-News, to study the predictive ability of the information contained in news texts on digital financial development in China.
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<p>Avatars are the alter-egos of users in Social Virtual Reality (SVR). They enable embodied interaction, preserving a wide spectrum of non-verbal and verbal communication cues in real-time, independent of users’ physical location. Avatar's appearance is highly variable as it spans from non to little human-like cartoonish forms to photorealistic replicas of real persons, leading to a wide range of potential effects other’s digital appearance has on the interpersonal relations established during an interaction.
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This dataset was derived from a questionnaire survey, including online surveys and field surveys, to test the reliability and validity of the media convergence perception scale. The questionnaire consisted of two parts. The first part was related to the 38 items generated in the prior step. The socio-demographic characteristic information of interviewees was captured in the second part. In addition, there was an additional question about whether respondents have used CLCM before, which is essential for the following data analysis.
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Social Media Big Dataset for Research, Analytics, Prediction, and Understanding the Global Climate Change Trends is focused on understanding the climate science, trends, and public awareness of climate change. The use of dataset for analytics of climate change trends greatly helps in researching and comprehending global climate change trends.
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Enterprise green innovation has emerged as an urgent concern for manufacturing companies in the current context of global green and sustainable development. China's "peak carbon emissions" and "carbon neutrality" goals require companies to take proactive measures to reduce carbon emissions and improve energy efficiency, with the application of digital technology playing a crucial role in this process.
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