CED Sentiment Data

1.Introduction This dashboard is aimed at providing a comprehensive data source that features the most important indicators related to the Chinese economy. The dashboard is divided into three sections, namely, sentiment data, high-frequency data, and low-frequency indicators. It will be updated on a monthly basis and the data can be downloaded directly from the webpage. General context The China Horizons project aims to contribute towards a better understanding of the Chinese economy and its impact on the global economy. The project seeks to achieve this goal by providing timely, accurate, and comprehensive data and analysis. The development of the dashboard is one of the tasks associated with this project, and it is expected to help researchers, policymakers, and other stakeholders to keep track of economic changes in China. 2.Methodological approach China’s Economy Data (CED) Platform The China’s Economy Data (CED) Platform is a web application that has been developed using the Python programming language. This platform is available online and provides users with access to a wide range of data related to the Chinese economy. The CED platform has been designed to be user-friendly and intuitive, with a simple interface that makes it easy for users to navigate and access the data they need. It is a comprehensive platform that features data related to various aspects of the Chinese economy, such as consumer and investment sentiment, inflation, employment among others. The platform is built on a robust database that is regularly updated with the latest economic data from various sources, including government agencies and international organizations. This ensures that users have access to accurate and up-to-date information. Sentiment Data The aim of this section is to collect relevant data and analyze it in order to gauge the overall sentiment of consumers and investors towards the Chinese economy. The consumer sentiment data has been derived by tracking user conversations on social media platform Weibo and analyzing them using the SNOWNLP sentiment analysis algorithm. This data has been collected across three main consumer categories - food, automobile, and fashion industry - and has been cleaned to remove irrelevant messages, ads, and noise. The sentiment has been calculated using the SnowNLP algorithm. The investment sentiment data, on the other hand, has been calculated based on news articles published in the Chinese media and analyzed using the https://huggingface.co/uer/roberta-base-finetuned-jd-binary-chinese algorithm. In addition to these, the China Horizons dashboard also includes the China Economic Policy Uncertainty Index, which has been calculated following the methodology presented by Hong-Kong Baptist University (https://cbade.hkbu.edu.hk/epu-mainland-china/). This index provides an indication of the level of uncertainty in the Chinese economy, and is an important indicator for investors and policymakers High-frequency Data In this section, we collect and process fast-changing publicly available data from different data sources such as National Bureau of Statistics, The People's Bank of China China Foreign Exchange Trade System Low-frequency Data Similarly to the High Frequency data we collect the data that is publish quarterly or less often, and we transform it to the format required by the platform. Among low-frequency data sources, we can find: Chinese Ministry of Financel, State Administration of Foreign Exchange &amp; National Bureau of Statistics,The People's Bank of China, China Ministry of Human Resources and Social Security, CEIC. 3.Summary of activities and/or research findings China’s Economy Data (CED) Platform platform that includes a dashboard, a database Data Update Pipeline a pipeline that ingests and processes the input data and updates the dashboard 4.Conclusions and future steps The platform gives a clear vision of key economic indicators in China. It will be updated once a month. 5.Bibliographical references (if applicable) Huang, Y., and Luk, P. (2019). “Measuring Economic Policy Uncertainty in China.” <em>China Economic Review</em>. Zhou, Bingqian, Yuhan Zhu and Xiabing Mao. “Sentiment Analysis on Power Rationing Micro Blog Comments Based on SnowNLP-SVM-LDA Model.” Highlights in Science, Engineering and Technology (2022): n. pag.1. 引言 本数据仪表盘（dashboard）旨在提供涵盖中国经济核心指标的综合性数据源。该仪表盘分为三大板块：情绪数据、高频数据与低频指标。数据将按月更新，用户可直接从网页端下载。 项目背景 中国洞察（China Horizons）项目旨在增进对中国经济及其对全球经济影响的理解。本项目通过提供及时、准确且全面的数据与分析来达成这一目标。本数据仪表盘的开发是该项目的任务之一，旨在助力研究人员、政策制定者及其他利益相关方及时追踪中国经济动态。 2. 研究方法 中国经济数据（China’s Economy Data, CED）平台 本平台是基于Python编程语言开发的网页应用程序，面向公众开放，为用户提供覆盖中国经济多领域的海量数据。平台设计兼具易用性与直观性，界面简洁易懂，便于用户快速浏览并获取所需数据。本平台涵盖中国经济各维度的相关数据，包括消费者与投资者情绪、通胀水平、就业情况等。平台依托稳定可靠的数据库，定期从政府机构、国际组织等多类数据源更新最新经济数据，确保用户可获取准确且实时的信息。 情绪数据板块 本板块旨在收集并分析相关数据，以衡量消费者与投资者对中国经济的整体情绪。消费者情绪数据通过追踪社交媒体平台微博（Weibo）上的用户对话，并使用SnowNLP情感分析算法（SnowNLP）进行处理得到。数据覆盖食品、汽车、时尚三大主要消费行业，已完成清洗以剔除无关信息、广告及噪声，最终通过SnowNLP算法计算得到情绪指数。投资者情绪数据则基于中国媒体发布的新闻文章，使用https://huggingface.co/uer/roberta-base-finetuned-jd-binary-chinese 算法分析计算得到。此外，中国洞察数据仪表盘还包含中国经济政策不确定性指数（China Economic Policy Uncertainty Index），该指数依照香港浸会大学（Hong-Kong Baptist University）提出的方法（https://cbade.hkbu.edu.hk/epu-mainland-china/）计算而成，可反映中国经济的不确定性水平，是投资者与政策制定者的重要参考指标。 高频数据板块 本板块收集并处理来自国家统计局、中国人民银行、中国外汇交易中心等多类数据源的实时公开快速变动数据。 低频数据板块 与高频数据板块类似，本板块收集发布频率为季度及以下的数据，并将其转换为平台所需的格式。低频数据源包括：中国财政部（Chinese Ministry of Finance）、国家外汇管理局、国家统计局、中国人民银行、人力资源和社会保障部以及CEIC数据库（CEIC）。 3. 项目活动与研究成果总结 中国经济数据（CED）平台 本平台包含数据仪表盘与数据库两大模块。 数据更新流水线 该流水线负责获取、处理输入数据并更新数据仪表盘。 4. 结论与未来展望 本平台清晰呈现了中国核心经济指标的全貌，将按月进行更新。 5. 参考文献（如适用） 1. Huang, Y. 与 Luk, P.（2019）：《Measuring Economic Policy Uncertainty in China》，刊载于《China Economic Review》。 2. Zhou, Bingqian、Yuhan Zhu 与 Xiabing Mao：《基于SnowNLP-SVM-LDA模型的电力限购微博评论情感分析》，刊载于《Highlights in Science, Engineering and Technology》（2022），页码未标注。