# Introduction Market Compass is an AI-driven search layer for Web3, utilizing AI and Big Data to analyze market sentiment and predict trends. At launch, Market Compass gathers data from X (formerly Twitter) and web scraping using Commune AI's [Subnet 17](/subnet/subnet-17). #### Links * Website: [https://marketcompass.ai](https://marketcompass.ai/) * X: * Github: # Vision At Market Compass, we envision a future where data is democratized, and every investor has the power to harness the collective intelligence of the market for informed decision-making. Our vision is to create a level playing field where access to comprehensive, real-time data is no longer a privilege reserved for a select few but a fundamental right for all participants in the digital asset ecosystem. **Mission Statement** Our mission is to democratize data access and empower investors with the tools and insights they need to engage in sentiment trading—a revolutionary approach to investment decision-making that leverages the sentiment and mindshare of the market to uncover hidden opportunities and mitigate risks. We are committed to analyzing a vast portion of data from diverse sources, including social media platforms, online communities, and news outlets, to provide our users with actionable insights and predictive analytics that drive success in the fast-paced world of cryptocurrency trading. **Guiding Principles** * **Democratization:** We believe in democratizing access to data and insights, breaking down barriers and empowering investors of all backgrounds to participate in sentiment trading and capitalize on market opportunities. * **Data-driven:** We are driven by data, leveraging advanced analytics and machine learning algorithms to analyze a large portion of data from multiple sources and extract meaningful insights that inform investment decisions. * **Transparency:** We prioritize transparency in our data collection and analysis processes, ensuring that our users have full visibility into the sources, methodologies, and implications of the data and insights we provide. * **Innovation:** We are committed to continuous innovation, pushing the boundaries of what's possible in sentiment trading and investment analytics to deliver value and drive success for our users. **Driving Impact** At Market Compass, we recognize the transformative potential of sentiment trading to revolutionize the way investors approach cryptocurrency markets. By democratizing data access and empowering investors with the tools and insights they need to engage in sentiment trading, we aim to drive positive impact by: * Empowering investors to make informed decisions and capitalize on market opportunities * Fostering greater transparency and accountability in the digital asset ecosystem * Democratizing access to investment opportunities and leveling the playing field for all participants * Driving innovation and growth in sentiment trading and investment analytics
# Goals and Audience **The Challenge of Early Identification of High-Potential Blockchain Technologies** In the fast-paced world of blockchain technologies, identifying high-potential projects at an early stage presents a significant challenge for investors. Market trends can shift rapidly, and distinguishing between fleeting fads and genuine innovations requires a deep understanding of the underlying technologies and market dynamics. At Market Compass, we recognize this challenge and are driven by the desire to provide investors with the tools and insights they need to stay ahead of the curve and capitalize on emerging opportunities.

Extended research

**Harnessing Collective Intelligence of Online Communities for Signal Detection** Online communities play a crucial role in shaping the narrative and direction of the blockchain industry. From social media platforms to discussion forums and messaging channels, these communities are hubs of collective intelligence, where valuable insights and signals can be gleaned from the conversations, opinions, and sentiments of participants. At Market Compass, we leverage advanced data gathering and analysis techniques to harness the collective intelligence of online communities for signal detection, enabling investors to uncover hidden opportunities and make informed investment decisions.
**Democratizing Access to Information and Investment Opportunities in Blockchains** Access to timely, accurate, and actionable information is essential for success in blockchain investments. However, traditional sources of information are often limited in scope and accessibility, leaving many investors at a disadvantage. Market Compass is committed to democratizing access to information and investment opportunities in blockchains by aggregating data from a wide range of sources, including social media, online communities, news outlets, and more. By providing subscribers with early access to promising projects and investment opportunities, we aim to level the playing field and empower investors of all backgrounds to participate in the digital asset ecosystem.

Sentiment trading

**Use Cases and Target Audience for MarketCompass.ai Platform** The MarketCompass.ai platform serves a diverse range of use cases and caters to a broad audience of investors and enthusiasts in the blockchain space. Whether you're a seasoned investor seeking to identify early-stage projects with high growth potential, a newcomer looking to explore investment opportunities in the blockchain industry, or a researcher interested in tracking market trends and sentiment analysis, Market Compass has something to offer. Our platform provides users with valuable insights, predictive analytics, and actionable intelligence that drive success in the dynamic and rapidly evolving world of blockchain investments.

Novice investor and educational use case

# Roadmap **Step 1: Foundation Establishment** * **Commune AI Mining Integration:** Integrate mining capabilities into Commune AI, our neural network subnet, to enhance data gathering efficiency and depth. * **Platform Development Kickoff:** Commence development of the Market Compass platform, focusing on building a robust foundation for data gathering, analysis, and user interface. * **Data Integration:** Integrate key data sources, including social media platforms, online communities, and news outlets, to fuel our predictive analytics engine. * **Feature Prototyping:** Prototype core features such as sentiment analysis, project evaluation, and portfolio tracking to lay the groundwork for future iterations.
**Step 2: Alpha Testing and Feedback Collection** * **Alpha Platform Launch:** Release the alpha version of Market Compass to a select group of early adopters for testing and feedback. * **User Feedback Collection:** Gather feedback from alpha users to identify areas for improvement and refinement. * **Iterative Development:** Continuously iterate and enhance platform features based on user feedback and market insights.
**Step 3: Beta Release and Optimization** * **Beta Platform Launch:** Roll out the beta version of Market Compass to a wider audience, offering expanded features and functionality. * **Performance Optimization:** Optimize platform performance and scalability to handle increasing data volumes and user traffic. * **Security Enhancements:** Implement robust security measures to safeguard user data and ensure platform integrity.
**Step 4: Full Platform Deployment and Community Building** * **Full Platform Launch:** Officially launch the full version of Market Compass to the public, offering comprehensive data analytics and investment tools. * **Community Building:** Foster a vibrant community of users, investors, and enthusiasts around Market Compass, encouraging collaboration and knowledge sharing. * **Continuous Innovation:** Stay ahead of the curve by continuously innovating and introducing new features and capabilities to meet the evolving needs of our users.
# Architecture At Market Compass, we leverage cutting-edge technology solutions to gather, analyze, and visualize data from various sources, providing our users with actionable insights for informed investment decisions. Here's an overview of our technology stack and the solutions we employ:
1. [**Data Gathering**](/tech-solutions/data-collection) * Utilizing mining activity on [Subnet 17](/subnet/subnet-17) on the Commune AI chain to gather data. * Querying the X (Twitter) API to collect real-time data on cryptocurrency-related topics. * Scraping data from 4chan, newsletters, Discord, and Telegram groups to capture diverse perspectives. * Storing collected data in a robust big data database for efficient retrieval and analysis. 2. [**Data Analysis**](/tech-solutions/data-analysis) * Analyzing data in different contexts, including project identification, narrative analysis, sentiment analysis, and distinguishing between fundamental data and marketing content. * Leveraging state-of-the-art AI models such as ChatGPT, Grok, Bard, Gemini, and others to extract valuable insights from the gathered data. * Assessing social sentiment through analysis of comments, views, and other engagement metrics. 3. [**Data Visualization**](/tech-solutions/data-visualization) * Presenting analyzed data in an easy-to-use platform interface for users to access and interpret. * Generating sentiment charts, narrative mindshare charts, and project mindshare charts to visualize trends and patterns. * Correlating price data with sentiment and mindshare to provide users with comprehensive insights into market dynamics. * Offering price prediction models based on sentiment analysis to aid users in making informed trading decisions. 4. **Trading Bot** * Integrating trading bots as a nice-to-have feature to automate trading based on sentiment analysis and market insights. * Empowering users to execute trades efficiently and capitalize on opportunities identified through our platform. ### **Technology Stack** * Programming Languages: Python, Node.js * Cloud Infrastructure: Amazon AWS (Amazon Web Services) * AI Models: ChatGPT, Grok, Bard, Gemini, and others * Data Sources: X (Twitter) API, 4chan, newsletters, Discord, Telegram groups * Database: Robust big data database for efficient data storage and retrieval # Data Collection At Market Compass, we employ a robust data gathering and storage system to collect and organize information from various sources, providing our users with comprehensive insights into the cryptocurrency market. Here's an overview of our data gathering process and the non-SQL database used for storage: ## **Data Gathering** 1. **Source Variety:** * We gather data from diverse sources, including social media platforms (such as X/Twitter), online forums (like 4chan), newsletters, Discord channels, Telegram groups, and more. * Each source provides a unique perspective and contributes to a comprehensive understanding of market sentiment and trends. 2. **Mining Activity:** * Our mining activity, facilitated through Subnet 17 on the Commune AI chain, collects real-time data from X (Twitter) API queries. * Miners receive different queries to perform every minute, ensuring a diverse and up-to-date dataset. * Queries are distributed among miners, each responsible for gathering data on specific cryptocurrency-related topics. 3. **Data Scrapping and Collection:** * In addition to X (Twitter) API queries, we utilize web scraping techniques to extract data from platforms like 4chan, newsletters, Discord, and Telegram. * This multi-source approach allows us to capture a wide range of opinions, sentiments, and discussions within the cryptocurrency community. ## **Non-SQL Database Storage** * **Choice of Database:** * We utilize a non-SQL (NoSQL) database for storing data. * NoSQL databases offer flexibility and scalability, making them well-suited for handling unstructured and semi-structured data, which is common in our data sources. * **Scalability and Performance:** * The non-SQL database architecture allows us to scale horizontally to accommodate growing data volumes and user demand. * This ensures optimal performance even as the dataset expands over time. * **Schema-less Design:** * NoSQL databases typically employ a schema-less design, allowing for agile development and adaptation to changing data structures. * This flexibility enables us to seamlessly integrate new data sources and modify existing schemas as needed. * **Data Indexing and Retrieval:** * We implement efficient indexing techniques to facilitate fast data retrieval and analysis. * Indexing enables quick access to relevant data points, empowering our analytics algorithms to generate insights in real-time. * **Data Replication and Redundancy:** * To ensure data durability and availability, we implement data replication and redundancy strategies within the non-SQL database architecture. * This redundancy mitigates the risk of data loss and provides fault tolerance in the event of hardware failures or system outages. # Data Analysis Market Compass utilizes several layers of analytical methods to extract actionable insights from data collected. Broadly, these include the following: ## **Contextual Analysis** We contextualize data by examining the underlying project it relates to, as well as the technology used, the stage of development, use cases, and traction. ## **Narrative Analysis:** We analyze the narrative surrounding each project, including media coverage, community discussions, and marketing efforts. ## **Sentiment Analysis** Sentiment analysis involves evaluating the sentiment expressed in social media posts, forum discussions, and other online interactions. We utilize natural language processing (NLP) and machine learning techniques to classify sentiments as positive, negative, or neutral. By gauging sentiment, we can assess market sentiment trends and identify sentiment-driven price movements. ## **Fundamental vs. Marketing Analysis** We distinguish between fundamental data, which pertains to a project's technological and economic fundamentals, and marketing content, which focuses on promotional efforts and community engagement. This differentiation allows us to assess the underlying value proposition of each project and discern between substance and hype. ## **Correlation Analysis** We explore correlations between different data points, such as sentiment and price movements, to identify potential predictive patterns. ## **Price Prediction Models** Leveraging machine learning algorithms and historical data, we develop price prediction models based on sentiment analysis and other relevant factors. # Data Visualization At Market Compass, we believe in the power of data visualization to empower users with actionable insights and intelligence. Through our individual dashboards and comprehensive filtering capabilities, users can explore and analyze cryptocurrency data with precision and ease. Here's how we enable users to uncover valuable insights through data visualization: **1. Individual Dashboards:** * We provide each user with a personalized dashboard tailored to their specific interests and preferences. * Users can customize their dashboards by selecting data filters, visualization options, and analytical tools to suit their investment strategies. **2. Advanced Filtering Options:** * Our platform offers advanced filtering options to allow users to refine their data queries based on various criteria. * Users can filter data by narrative, project, token, data source, X (Twitter) account, influencers, and data types (fundamental analysis vs. marketing content). **3. Overall Sentiment Analysis:** * We present users with an overall sentiment analysis, indicating the general sentiment within the cryptocurrency market. * This high-level overview helps users gauge market sentiment trends and sentiment-driven price movements. **4. Narrative Sentiment Analysis:** * Users can explore sentiment analysis results specific to different narratives within the cryptocurrency ecosystem. * By analyzing narrative sentiment, users can identify leading narratives and assess their impact on market dynamics. **5. Project Sentiment Analysis:** * Our platform provides sentiment analysis for individual blockchain projects, allowing users to evaluate the sentiment surrounding each project. * Users can identify projects with positive sentiment trends and potential for future growth and adoption. **6. Narrative Mindshare:** * We offer insights into narrative mindshare, highlighting which narratives are currently dominating discussions within the cryptocurrency community. * Users can identify emerging narratives and assess their relevance to investment opportunities. **7. Project Mindshare:** * Users can explore project mindshare data to identify leading projects within each narrative. * This information helps users discover new and under-the-radar projects with high potential for future growth. **8. Price Prediction:** * Our platform provides price prediction models based on historical data and sentiment analysis. * Users can leverage these predictive models to anticipate future price movements and make informed investment decisions. # $AIM Token The $AIM token will be deployed on the **Base** network. Contract Address: [**0x97b959385dfDCAf252223838746Beb232AC601Aa**](https://basescan.org/address/0x97b959385dfDCAf252223838746Beb232AC601Aa) ## Tokenomics
RoundPercentagePriceFDVCliff (m)No. Tokens
Pre-seed - Burned20%0.01$1,000,0001220000000
Seed10%0.02$2,000,000010000000
Private10%0.027$2,700,000010000000
Public50%0.038$3,800,000050000000
Liquidity5%--05000000
Team - Burned5%--125000000
Burn 135,45%--35458506
Burn 225,00%--25000000
Total Burned60.45%--60458506
## Circulating supply **39,541,494** $AIM ## Total supply **39,541,494** $AIM ## Release schedule **02.07.2025** - 25,000,000 $AIM\ \ Team lock: \ Pre-seed lock: ## Burned supply Not allocated public sale coins burn TX: Team tokens and pre-seed burn TX: ## Fund Raising ~~**$200,000** in $COMAI in Pre-seed round. Incubated by:~~ [~~https://twitter.com/comswap\_io~~](https://twitter.com/comswap_io) **$200,000** in Seed round: Secured **$270,000** in Private round: Secured **$552,576** Hard Cap in public round: Secured\ \ **$822,576** in Total. # Subnet 17 Market Compass utilizes Commune AI, specifically Subnet 17, to gather real-time data from X (Twitter) at scale. Here's how the subnet operates: 1. **Query Creation:** * Queries are created to access the X (Twitter) API, targeting market-related topics. 2. **Query Distribution:** * Miners within Subnet 17 receive a unique query to perform every minute, just before each voting cycle begins. 3. **Query Validation:** * Miners return updates for all queries, ensuring that the data collected is fresh and relevant. * Trust is placed in miners by default, assuming they provide accurate and valid data. 4. **Backend Verification:** * An undisclosed endpoint in our backend verifies random queries with timestamps provided by miners. * If the response differs from the expected data, the miner is blacklisted, ensuring data integrity. 5. **New Miner Validation:** * New miners undergo validation checks upon their first request to ensure data accuracy and reliability. 6. **Scoring System:** * The scoring system rewards miners for providing valid data, with emission distributed evenly among valid miners. * This approach builds a resource base necessary for future development and expansion. # Mining Guide {% hint style="warning" %} Miners operating multiple machines with the same API key should avoid sending multiple requests simultaneously, as this may lead to rate-limiting. {% endhint %} Welcome to the Market Compass Subnet 17 Mining Guide! In this guide, you'll learn how to set up and deploy a mining node on Subnet 17 to contribute to the data gathering process for Market Compass. Let's get started: ## **Prerequisites** Before diving into the mining process, ensure you have the necessary environment variables set up: 1. **MC\_BEARER\_TOKEN:** Bearer token for Twitter Pro API. Export this variable with your X (Twitter) API token. ```markup export MC_BEARER_TOKEN=AAA... ``` 2. **MC\_SUBNET\_API\_X\_API\_KEY:** Market Compass API key for validators. Contact us via Discord-ticket on the Subnet 17 Discord Server to obtain a new API key. ```markup export MC_SUBNET_API_X_API_KEY= ``` 3. **MC\_SUBNET\_API\_URL:** URL to the current version of the used API. Set this variable to the appropriate API URL. ```markup export MC_SUBNET_API_URL=https://api3.subnet.marketcompass.ai ``` ## **Dependencies** Ensure you have the necessary dependencies installed. The key dependency is the CommuneX library. You can find the full dependency list in the [requirements.txt](https://github.com/MarketCompassDev/marketcompass-subnet/blob/main/requirements.txt) file. Here are the main dependencies: * communex * typer * uvicorn * keylimiter * pydantic-settings ## **Miner Setup** Follow these steps to set up and register your miner on Subnet 17: 1. **Run Miner:** From the root of your project, run the following command to start the miner: ```markup comx module serve subnet.miner.model.Miner --subnets-whitelist 17 --ip 0.0.0.0 --port 8000 ``` 2. **Register Miner:** Register your miner using the following command: ```markup comx module register --ip --port 8000 --netuid 17 ``` ## Miner Code {% embed url="" %} Miner code {% endembed %} ```python import os import requests from communex.module import Module, endpoint from communex.key import generate_keypair from keylimiter import TokenBucketLimiter class Miner(Module): def __init__(self): super().__init__() self.bearer_token = os.getenv('MC_BEARER_TOKEN') @endpoint def generate(self, prompt: str, start_time: str = '2024-04-01T5:00:00Z', max_results: int = 50): # TODO: pass start_time, max_results from validator url = "https://api.twitter.com/2/tweets/search/all" def bearer_oauth(r): r.headers["Authorization"] = f"Bearer {self.bearer_token}" r.headers["User-Agent"] = "v2FullArchiveSearchPython" return r response = requests.request("GET", url, auth=bearer_oauth, params={ 'query': prompt, "max_results": max_results, "start_time": start_time, "user.fields": "id,username,name", "tweet.fields": "created_at,author_id" }) if response.ok: tweets = response.json() return tweets['data'] raise Exception(f"Cant get tweets for prompt '{prompt}'") if __name__ == "__main__": from communex.module.server import ModuleServer import uvicorn key = generate_keypair() miner = Miner() refill_rate = 1 / 400 bucket = TokenBucketLimiter(2, refill_rate) server = ModuleServer(miner, key, ip_limiter=bucket, subnets_whitelist=[17]) app = server.get_fastapi_app() # Only allow local connections uvicorn.run(app, host="0.0.0.0", port=8000) ``` ## **Validator Setup** To validate and register your miner, follow these steps: 1. **Run Validator:** Execute the validator script to initiate validation: ```markup python3 -m market-compass-subnet.subnet.cli ``` 2. **Register Validator:** Register your validator using the following command: ```markup comx module register market-compass:: --netuid 17 ``` ## **Further Reading** For more information and documentation on the Commune AI ecosystem and subnet details, please visit the [Official Commune Page](https://commune.ai/) and its developer documentation. Congratulations! You've successfully set up and deployed your mining node on Subnet 17. Your contributions will play a crucial role in gathering valuable data for Market Compass, empowering users with actionable insights and intelligence in the cryptocurrency market. # Follow us * [**Website**](https://marketcompass.ai/) * [**X (Twitter)**](https://twitter.com/marketcompassai) * **Community Discord (Coming Soon)** * **Public Sale (Coming Soon)**