Dataset: Finance Subreddits

About this Dataset

Finance Subreddits

Context

Interested in text data about financial topics? That's the dataset for you! In this dataset, I've group posts from the major finance subreddits (r/investing, r/finance, r/options, ...)

Content

Reddit posts from various subreddits, downloaded using praw (The Python Reddit API Wrapper) and the pushshift API.

Inspiration

How can I use all this data?

Perform sentiment analysis, such as detecting fear or hype in the market
Topic modeling
Follow the trends
and all kind of other tasks related to NLP

Tables

Algotrading Subreddit

@kaggle.paolodelia_finance_subreddits.algotrading_subreddit

6.7 MB
21098 rows
8 columns


CREATE TABLE algotrading_subreddit (
  "unnamed_0" BIGINT,
  "id" VARCHAR,
  "title" VARCHAR,
  "url" VARCHAR,
  "created_utc" BIGINT,
  "score" BIGINT,
  "num_comments" BIGINT,
  "selftext" VARCHAR
);

Finance Subreddit

@kaggle.paolodelia_finance_subreddits.finance_subreddit

26.75 MB
216865 rows
8 columns


CREATE TABLE finance_subreddit (
  "unnamed_0" BIGINT,
  "id" VARCHAR,
  "title" VARCHAR,
  "url" VARCHAR,
  "created_utc" DOUBLE,
  "score" DOUBLE,
  "num_comments" DOUBLE,
  "selftext" VARCHAR
);

Investing Subreddit

@kaggle.paolodelia_finance_subreddits.investing_subreddit

76.87 MB
219504 rows
8 columns


CREATE TABLE investing_subreddit (
  "unnamed_0" BIGINT,
  "id" VARCHAR,
  "title" VARCHAR,
  "url" VARCHAR,
  "created_utc" DOUBLE,
  "score" DOUBLE,
  "num_comments" DOUBLE,
  "selftext" VARCHAR
);

Options Subreddit

@kaggle.paolodelia_finance_subreddits.options_subreddit

17.8 MB
59273 rows
8 columns


CREATE TABLE options_subreddit (
  "unnamed_0" BIGINT,
  "id" VARCHAR,
  "title" VARCHAR,
  "url" VARCHAR,
  "created_utc" BIGINT,
  "score" BIGINT,
  "num_comments" BIGINT,
  "selftext" VARCHAR
);

Stockmarket Subreddit

@kaggle.paolodelia_finance_subreddits.stockmarket_subreddit

25.82 MB
72620 rows
8 columns


CREATE TABLE stockmarket_subreddit (
  "unnamed_0" BIGINT,
  "id" VARCHAR,
  "title" VARCHAR,
  "url" VARCHAR,
  "created_utc" BIGINT,
  "score" BIGINT,
  "num_comments" BIGINT,
  "selftext" VARCHAR
);