Social analysis tool for cryptocurrencies.
Create a Python 3.8 virtual environment and run the following command:
pip install -r requirements.txt
List of the 18 cryptocurrencies that have been analyzed.
| BTC | ETH | BNB | USDT | SOL | ADA | XRP | DOT | LUNA |
| DOGE | AVAX | SHIB | CRO | MATIC | WBTC | ALGO | LTC | UNI |
| Method | Description |
|---|---|
| list_all_coins() | List all available coins in Santiment |
| get_price() | Price (USD) |
| get_volume() | Volume (USD) |
| get_daily_trading_volume() | Daily trading volume (USD) |
| get_marketcap() | Market Cap (USD) |
| get_social_volume() | Social volume based on platform (Twitter, Reddit, Telegram, BitcoinTalk) |
| get_sentiment_balance() | Sentiment balance of a coin |
| get_social_dominance() | Social dominance of a coin |
| get_sentiment() | Sentiment score (positive / negative) |
| get_development_activity() | Development activity |
| get_github_activity() | Github activity |
| get_active_addresses_24h() | On-Chain Active addresses (24h) |
| get_exchange_balance() | On-Chain Exchange_balance |
| get_network_growth() | On-Chain Network growth |
| get_transaction_volume() | On-Chain Transaction volume |
| get_perpetual_funding_rate() | On-Chain Perpetual funding rate |
| get_circulation() | On-Chain Circulation supply |
| get_velocity() | On-Chain Velocity |
| get_withdrawal_transactions() | On-Chain Withdrawal transactions |
Here is a short description for the LunarCrush API v2 endpoints and their respective methods. You can find more details about the request parameters here
| Method | Description |
|---|---|
| get_assets() | Details, overall metrics, and time series metrics for one or multiple assets. |
| get_market_pairs() | Provides the exchange information for assets, and the other assets they are being traded for. |
| get_market() | Summary information for all supported assets (Markets page) including 5 recent time series values for some metrics. |
| get_global() | Overall aggregated metrics for all supported assets (top of Markets page). |
| get_meta() | Meta information for all supported assets |
| get_exchanges() | Meta information for all exchanges that we track |
| get_exchange() | Meta information and market pairs for a single exchange that we track |
| get_coin_of_the_day() | The current coin of the day |
| get_coin_of_the_day_info() | Provides the history of the coin of the day on LunarCRUSH when it was last changed, and when each coin was last coin of the day |
| get_feeds() | Social posts, news, and shared links for one or multiple coins. |
| get_influencers() | List of social accounts that have the most influence on different assets based on number of followers, engagements and volume of posts. |
| get_influencer() | Individual influencer details including actual posts. |
| Metric | Description |
|---|---|
| GALAXY SCORE | The Galaxy Score™ indicates how healthy a coin is by looking at combined performance indicators across markets and social engagement. Display the real-time Galaxy Score™ of any coin. |
| ALT RANK | AltRank™ measures a coin's performance VS. all other coins that we actively support. In general, it is a unique measurement that combines ALT coin price performance relative to Bitcoin and other social activity indicators across the entire crypto market. A coin can have a high AltRank of 1 even in a bear market situation. |
| INFLUENCERS | View Twitter influencer activity and their impact across all coins and tokens. All influencers are measured by the same metrics, which includes followers, replies, favorites, and retweets. Metrics are evaluated across all collected posts during the timeframe selected. Actual influence will vary over time and will depend on user activity. |
| CANDLESTICK | The incredibly powerful Candlestick widget takes any data point and compares it to price over a specified timeframe. |
| WORD CLOUD | Uncover keywords used throughout collected social content for any coin. The Word Cloud is generated from all recent and available social posts from Twitter and Reddit. It looks at frequency of mentions. All data is segmented by either all coins or specific, individual coins. |
| SOCIAL FEED | Display social feeds from multiple sources including Twitter, Reddit, news channels and more all at once. Gain unique insights into what's being talked about in real time. All social feeds have been cleaned with spam removed and can be organized by coin. |
Simple API wrapper for some methods from tweepy.
| Method | Description |
|---|---|
| get_user() | Request user information. |
| get_all_tweets() | Request all tweets given a query (Academic Research only). |
| get_recent_tweets() | Request recent tweets given a query. |
| get_all_tweets_count() | Request all twitter count given a query (Academic Research only). |
| get_recent_tweets_count() | Request recent twitter counts given a query. |
Asynchronous Twitter scraper is based on twint project configuration. New parameters have been added to parallelize the scraping process and filter some information. The rest of the parameters can be found in the configuration file.
| Additional twint parameters | Type | Description |
|---|---|---|
| Users | dict | Dictionary to store the coins and their respective users (parallelization purposes). |
| Queries | dict | Dictionary to store the coins and their respective queries (parallelization purposes). |
| Save_replies | bool | True to store the replies of a tweet. |
| Save_mentions | bool | True to store the mentions of a tweet. |
| Save_meta | bool | True to store all the information of the tweets. |
| Remove_mentions | bool | Remove tweet mentions. |
Simple API Wrappers with an example endpoint request.
- Glassnode API: Parameter parsing and requesting.
- Kraken-Futures API: Parameter parsing and requesting.
These APIs have been considered for getting on-chain data but have not been used in the final project.
You can find the complete interactive dashboard here
Comparison for all 18 coins based on 5 different analysis (price, market cap., social influence, on-chain and developer activity).
In-depth analysis of key social metrics and interactive study of correlation between price and social talk volume, per coin and month.
Tool that helps to estimate a Token A price if it had the Market Capitalization of a Token B.
Natural Language Processing of all the tweets in the last 3 months from the top 10 influencers of each coin
├── LICENSE
├── README.md
├── requirements.txt
│
├── data
│ ├── dashboard1 <- Data scraped for dashboard 1 (General Overview).
│ ├── dashboard2 <- Data scraped for dashboard 2 (Social Impact Analysis).
│ ├── dashboard3 <- Data scraped for dashboard 3 (Perspectivizer).
│ └── dashboard4 <- Data scraped for dashboard 4 (NLP for tweets).
│
├── images <- Sample images generated from the dashboards.
│
├── main.py <- Main script containing all the scraping and dashboard generation pipeline.
├── dashboard.py <- Data processing and dataframe creation for dashboards.
├── utils.py <- Util functions.
│
├── nlp <- Module for Natural Language Processing (NLP).
│ ├── parsers.py <- Data processing for parsing and cleaning scraped tweets.
│ ├── pipeline.py <- Pipeline for tokenization and word counting.
│ └── sentiment.py <- Sentiment analysis functions.
│
├── scrapers <- Module containing the scrapers.
│ ├── twint <- Twint repository with custom modifications.
│ │
│ ├── __init__.py <- Makes scrapers a Python module.
│ ├── glassnode.py <- Glassnode simple wrapper.
│ ├── kraken.py <- Kraken-Futures simple wrapper.
│ ├── lunarcrush.py <- Lunarcrush wrapper.
│ ├── santiment.py <- Santiment wrapper.
│ ├── tickers.py <- Dictionary containing the tickers and their possible written representations.
│ └── twitter.py <- Twitter wrappers (tweepy / parallel twint).
│
└── _config.py <- Create your own _config.py file to store the API KEYS