One of the most distinctive features of the internet era is the big data generated by online users, where the contained information is often believed to provide added value to financial and real sectors. Among various types of big data, posts expressing opinions or sharing experiences on social media platforms are frequently observed, particularly in the financial industry. Due to the high reliance on information among financial practitioners, posts on financial social media platforms often exert significant influence on investors' financial decisions.
Posting serves as the primary form of social interaction for investors on online platforms. Investor posts mainly involve sharing perspectives, commenting on others' posts, raising questions, and responding to inquiries. Research indicates three primary motivations for investors to post on social platforms. First, investors post to facilitate effective information interaction. Posting on social platforms encourages more investors to engage in discussions and responses, enabling them to obtain valuable feedback. Second, investors may post to achieve self-actualization, as posters hope to attract followers by sharing compelling content and aspire to become opinion leaders, demonstrating their investment capabilities to expand influence. Third, investors post to express and incite emotions, particularly when their investment performance is unsatisfactory.
The Snowball Investor Post/Comment Data for Hong Kong listed companies launched by CnOpenData primarily consists of textual content, directly presenting post details. It includes multiple fields such as stock code(股票代码), poster ID/nickname(帖子发表者id/昵称), post source and time(发布来源及时间), likes count(点赞量), reposts count(转发量), and comments count(评论数).
Time Coverage
As of May 2024
Field Display
Sample Data
Data Update Frequency
Annual updates