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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis
| Date | Stars |
|---|---|
| 2026-07-24 | 2520 |
| 2026-07-25 | 2520 |
| 2026-07-28 | 2520 |
| 2026-07-30 | 2520 |
| 2026-08-06 | 2520 |
Today
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Momentum
0.0
growth rate 0.00%/day
<img src="/docs/stocksight.png?raw=true" alt="stocksight" />
[](./LICENSE)
[](https://github.com/shirosaidev/stocksight/releases/latest)
[](https://www.patreon.com/shirosaidev)
[](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=CLF223XAS4W72)
# stocksight
Stock market analyzer and stock predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis. How much do emotions on Twitter and news headlines affect a stock's price? Let's find out...
## About
stocksight is an open source stock market analysis software that uses Elasticsearch to store Twitter and news headlines data for stocks. stocksight analyzes the emotions of what the author writes and does sentiment analysis on the text to determine how the author "feels" about a stock. It could be used for more than finding sentiment of just stocks, it could be used to find sentiment of anything...
## Slack workspace
Join the conversation, get support, etc on [stocksight Slack](https://join.slack.com/t/stocksightworkspace/shared_invite/enQtNzk1ODI0NjA3MTM4LTA3ZDA0YzllOGNiM2I5ZjAzYWM2MjNmMjI0OTRlY2ZjYTk1NmM5YmEwMmMwOTE2OTNiMGZlNzdjZmZkM2RjM2U).
## Requirements
- Python 3.x
- Elasticsearch 5.x
- Kibana 5.x
- elasticsearch python module
- nltk python module
- requests python module
- tweepy python module
- beautifulsoup4 python module
- textblob python module
- vaderSentiment python module
- newspaper3k python module
### Download
```shell
$ git clone https://github.com/shirosaidev/stocksight.git
$ cd stocksight
```
[Download latest version](https://github.com/shirosaidev/stocksight/releases/latest)
## Screenshot
Stocksight Kibana dashboard
<img src="https://github.com/shirosaidev/stocksight/blob/master/docs/stocksight-dashboard-kibana.png?raw=true" alt="stocksight kibana dashboard" />
## Install - Docker
*** **See [how to use](#how-to-use) below before building the Docker containers** ***
1) Download/clone stocksight repo with git.
2) Set up stocksight, elasticsearch and kibana containers using Docker compose
```
cd stocksight
cp config.py.sample config.py
***see how to use below for config.py (stocksight config) changes***
docker-compose build && docker-compose up
```
**This will volume mount config.py (stocksight settings) and twitteruserids.txt to those files in your local git cloned "stocksight" directory**
3) Once all the containers have started up, shell into the container
`docker exec -it stocksight_stocksight_1 bash`
4) See examples below for running stocksight.
## Install - local
**Recommended to install Elasticsearch and Kibana in local machine or other machine/vm/docker**
1) Install python requirements using pip
`pip install -r requirements.txt`
2) Install python nltk data
`python -c "import nltk; nltk.download('punkt'); nltk.download('stopwords')"`
## How to use
1) Create a new twitter application and generate your consumer key and access token. https://developer.twitter.com/en/docs/basics/developer-portal/guides/apps.html
https://developer.twitter.com/en/docs/basics/authentication/guides/access-tokens.html
2) Copy config.py.sample to config.py (stocksight config file)
3) Set elasticsearch settings in config.py for your env (for Docker, set `elasticsearch_host = "elasticsearch"`)
4) Add twitter consumer key/access token and secrets to config.py
5) Edit config.py and modify NLTK tokens required/ignored and twitter feeds you want to mine. NLTK tokens required are keywords which must be in tweet before adding it to Elasticsearch (whitelist). NLTK tokens ignored are keywords which if are found in tweet, it willExcerpt of 8,983 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:d26af4030508d5f2, topic:natural-language-processing, topic:sentiment-analysis, desc:natural language processing