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Reddit Financial Forum Sentiment and NLP Data
Reddit & Forum Data
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About
Analysing community sentiment and engagement within high-activity online financial forums provides a window into modern retail investor behaviour. These records capture the most popular interactions from the SuperStonk subreddit, a digital space currently experiencing significant activity. By tracking top comments and posts, researchers can observe how specific narratives gain traction and how the community reacts to market-moving events in real-time. This resource is essential for decoding the language and momentum of digital investment communities. Monitoring these digital interactions is akin to listening to the roar of a stadium crowd; while individual voices provide detail, the collective volume and tone reveal the true state of the game.
Columns
- index: A sequential numerical identifier assigned to each record.
- title: The heading or subject line of the Reddit post.
- score: The upvote score of the post, indicating community agreement or interest levels.
- id: The unique identifier for the specific poster or entry.
- url: The direct web address link to the original Reddit post.
- comms_num: The total number of comments associated with the post.
- created: The time of creation recorded in Unix Epoch format.
- body: The main text content or body of the post.
- timestamp: The date and time the entry was recorded, provided in a standard date-time format.
Distribution
The information is delivered in a CSV file titled
Superstonk_Top_Comments.csv with a file size of approximately 1.2 MB. The collection consists of 1,949 valid records across 9 distinct columns. Analysis shows 100% validity for core fields like index, score, and timestamp, though some fields like URL and body text contain missing values due to the variety of post formats on the platform. The data is structured for immediate analytical use and is updated on a monthly basis.Usage
This resource is ideal for performing sentiment analysis and natural language processing (NLP) to identify trending topics among retail investors. It is well-suited for exploratory data analysis (EDA) to understand how engagement metrics like upvotes correlate with post volume. Additionally, users can apply these records to study the lifecycle of viral financial discussions or to build predictive models regarding community interest in specific market entities.
Coverage
The scope of the records covers the top-performing content from the SuperStonk subreddit over a 30-day window. Geographically, the data reflects a global user base, while the temporal range for this specific snapshot spans from 4 March 2022 to 3 April 2022. Demographic coverage is focused entirely on the active participants within this specific online financial community. Note that while most fields are populated, the "url" and "body" columns have missing data for approximately 49% and 38% of records respectively, depending on the post type.
License
CC0: Public Domain
Who Can Use It
Data analysts and beginners can leverage these records to refine their skills in text mining and social media analytics. Financial researchers might utilise the data to gauge the influence of retail sentiment on market trends. Furthermore, educators can find this a valuable primary source for demonstrating real-world applications of NLP and exploratory data techniques on high-activity social media datasets.
Dataset Name Suggestions
- SuperStonk Community Sentiment and Top Comment Archive
- Retail Investor Discourse: SuperStonk Engagement Metrics
- Reddit Financial Forum Sentiment and NLP Data
- Monthly SuperStonk Interaction and Trending Post Index
- High-Activity Financial Subreddit Commentary Records
Attributes
Original Data Source: Reddit Financial Forum Sentiment and NLP Data
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Free
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