Social Sciences
This study investigates whether the ingredients listed on restaurant menus can provide insights into a city's socioeconomic status. Using data from an online food delivery system, the study compares menu items with local education rates and rental prices. A machine learning model is developed to predict menu prices based on ingredients and socioeconomic factors. An efficiency metric is proposed to cluster restaurants to address autocorrelation, comparing ingredient averages to socioeconomic indicators.
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296 Views
Data were collected through the Twitter API, focusing on specific vocabulary related to wildfires, hashtags commonly used during the Tubbs Fire, and terms and hashtags related to mental health, well-being, and physical symptoms associated with smoke and wildfire exposure. We focused exclusively on the period from October 8 to October 31, aligning precisely with the duration of the Tubbs Fire. The final dataset available for analysis consists of 90,759 tweets.
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335 Views
The dataset explores the linguistic characteristics of Ukrainian online community members on "Lviv. Forum Ridne City" (https://misto.ridne.net/) based on gender (female/male). It includes vectors of male and female profiles, along with 36 control vectors for 18 women's profiles and 18 men's profiles. The dataset includes 48 linguistic characteristics of gender in online communication. The linguistic features analyzed encompass a wide range, including apology, modal designs, emotions, profanity, sports and politics references, and more.
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142 Views
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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1458 Views
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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37 Views
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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19 Views
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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60 Views
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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1090 Views
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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265 Views
<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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27 Views