Dataset: Stock Comments (Twits) - Tinkoff Pulse

About this Dataset

Stock Comments (Twits) - Tinkoff Pulse

Hello there!

This is my data, which I've used for my bachelor diploma research in 2024 at HSE University. I have parsed all comments (or you can call them stock twits) from T-pulse threads from 01 JAN 2019 (launch of the platform) to 30 MARCH 2024. A total of 10 tickers were taken: SBER, GAZP, YNDX, TCSG, SGZH, PIKK, RTKM, MVID, KMAZ, BANE. During the chosen period, there were changes in the CCP of the Bank of Russia, the introduction of sanctions by Western countries against the Russian Federation.

Language: Russian (mostly) and English

Columns

inserted - date of posting of a comment (or post);
likesCount - amount of likes under comment (or post);
commentsCount - amount of comments under comment (or post);
text - raw text of a parsed comment (you should probably clean it from emoji etc);
reactions_counters - list of dicts with type and amount of reactions under comment. There are emoji-like reactions like "rocket", "like", "dislike", "not-convinced", "buy-up".

Additionally
I have added df_labelled_llm.csv dataset with labelled posts. Around 1000 from each ticker mentioned above, so total is around 10K posts. Labelling was done 90% with LLM and 10% manually for slang posts. You can use this as a starting point of your research.

Areas of application

Sentiment analysis of stock twits;
Fine-tuning BERT-based models;
Testing algotrading strategies based on sentiment analysis;
Research.

This data was gathered for educational purposes only. No exact names, phone numbers or addresses of the authors of posts/comments were included into the dataset.

Tables

Df Bane Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_bane_data

5.87 MB
8187 rows
5 columns


CREATE TABLE df_bane_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Gazp Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_gazp_data

105.45 MB
263340 rows
5 columns


CREATE TABLE df_gazp_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Kmaz Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_kmaz_data

7.83 MB
15786 rows
5 columns


CREATE TABLE df_kmaz_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Labelled Llm

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_labelled_llm

2.89 MB
10108 rows
2 columns


CREATE TABLE df_labelled_llm (
  "text_preprocessed" VARCHAR,
  "label" VARCHAR
);

Df Mvid Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_mvid_data

9.2 MB
18840 rows
5 columns


CREATE TABLE df_mvid_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Pikk Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_pikk_data

14.1 MB
28699 rows
5 columns


CREATE TABLE df_pikk_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Rtkm Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_rtkm_data

14.49 MB
19578 rows
5 columns


CREATE TABLE df_rtkm_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Sber Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_sber_data

107.32 MB
244255 rows
5 columns


CREATE TABLE df_sber_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Sgzh Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_sgzh_data

18 MB
52045 rows
5 columns


CREATE TABLE df_sgzh_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Tcs Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_tcs_data

45.42 MB
118998 rows
5 columns


CREATE TABLE df_tcs_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);

Df Yndx Data

@kaggle.ilovebeer228_stock_comments_twits_tinkoff_pulse.df_yndx_data

66.75 MB
184287 rows
5 columns


CREATE TABLE df_yndx_data (
  "inserted" TIMESTAMP,
  "likescount" BIGINT,
  "commentscount" BIGINT,
  "text" VARCHAR,
  "reactions_counters" VARCHAR
);