Chinese listed companies release daily market updates on major financial platforms and establish interactive communication platforms for investors. Investors nationwide engage in discussions through posts and replies on these online stock forums, generating an immense corpus of text data related to Chinese stock market investments. Researchers can leverage this vast dataset to examine multi-dimensional information such as market judgments and individual sentiments of investors.
In recent years, researchers domestically and internationally have discovered:
Media text sentiment can more accurately gauge shifts in investor sentiment within China's stock market, exhibiting significant in-sample and out-of-sample predictive power for stock returns. Media text sentiment also demonstrates substantial predictive capability for key macroeconomic indicators, holding significant academic and practical application value.
— Jiang Fuwei, Meng Lingchao, Tang Guohao: "Media Text Sentiment and Stock Return Prediction," China Economic Quarterly, Issue 04, 2021.
To facilitate academic research, CnOpenData conducts quantitative and content-level (sentiment analysis) statistical processing on both post and reply data from A-share listed company stock forums. This includes fields such as security code, company name, posting period, post volume, proportion of positive/negative posts, and counts of positive/negative posts, providing high-quality data support for relevant studies.
Data Features
- Temporally, this dataset primarily covers forum posts and replies since 2008, with timestamps categorized into five distinct periods: pre-market opening, morning trading session, lunch break, afternoon trading session, and post-market closing.
- In terms of data volume, the dataset encompasses approximately 330 million main posts and 420 million replies, representing an ultra-large-scale text corpus.
- Regarding field richness, beyond aggregating post/reply statistics per company and time period, the data incorporates sentiment analysis for each post/reply using the Chinese Financial Sentiment Dictionary. This reveals annual counts and proportions of positive, negative, and neutral posts/replies per company.
Time Coverage
- Posting Period: 1988-2024
- Replying Period: 2007-2024
Field Display
Sample Data
A股上市公司股吧发帖文本统计数据
A股上市公司股吧回帖文本统计数据
Relevant Literature
- Zheng Jiandong, Lü Xiaoliang, Lü Bin, Guo Feng, 2022: "Information Interaction on Social Media Platforms and Capital Market Pricing Efficiency—Evidence from Big Data on Stock Forum Discussions," Journal of Quantitative & Technological Economics, Issue 11.
- Yin Bichao, Kong Dongmin, Ji Mianmian, 2022: "Does Retail Investor Activism Improve Audit Quality of Listed Companies?," Accounting Research, Issue 10.
- Fan Xiaoyun, Wang Yedong, Wang Daoping, Guo Wenxuan, Hu Xuanyi, 2022: "Heterogeneity Analysis of Information Content from Different Financial Text Sources—Based on a Hybrid Text Sentiment Measurement Method," Management World, Issue 10.
- Zhu Mengnan, Liang Yuheng, Wu Zengming, 2020: "Internet Information Interaction Networks and Stock Price Crash Risk: Public Opinion Supervision or Irrational Contagion," China Industrial Economics, Issue 10.
- Sun Kunpeng, Wang Dan, Xiao Xing, 2020: "Internet Information Environment Regulation and the Corporate Governance Role of Social Media," Management World, Issue 7.
- Wang Dan, Sun Kunpeng, Gao Hao, 2020: "The Impact of 'Voting by Voice' on Social Media on Management's Voluntary Earnings Forecasts," Journal of Financial Research, Issue 11.
- Bu Hui, Xie Zheng, Li Jiahong, Wu Junjie, 2018: "The Influence of Investor Sentiment Based on Stock Comments on the Stock Market," Journal of Management Sciences in China, Issue 4.
- Chang, Yen-Cheng; Hong, Harrison G.; Tiedens, Larissa; Wang, Na; Zhao, Bin, 2015: “Does Diversity Lead to Diverse Opinions? Evidence from Languages and Stock Markets,” Rock Center for Corporate Governance at Stanford University Working Paper No. 168, Stanford University Graduate School of Business Research Paper No. 13-16.
- Sheridan Titman, Chishen Wei, Bin Zhao, 2021: “Corporate Actions and the Manipulation of Retail Investors in China: An Analysis of Stock Splits,” Journal of Financial Economics.
Data Update Frequency
Annual updates