Social Critical Mass Graph – MediaBubbles

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Alex Blagirev
Project Owner

Social Critical Mass Graph – MediaBubbles

Funding Requested

$120,000 USD

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Overview

Critical Mass includes knowledge base and correlations over narrative, engagement, reactions, intersection, messaging, and activities for multiple segments and industries like DeFi. MediaBubbles is a platform that merges social public data from multiple sources and places it on the Knowledge Layer. The knowledge Layer provides an interface for users to get answers to questions related to social data and their research and help to understand the dependencies.

Proposal Description

Our Team

Our team possesses significant experience in AI and Data Management, with a track record of successful projects utilizing social data and sentiment analysis. We have a strong background in technology and programming, with a deep understanding of domain-specific challenges. Our commitment to delivering exceptional user experiences is backed by a history of proven results and multiple international awards in innovation, data management, fintech, and crypto.

View Team

Company Name (if applicable)

Mediabubbles

Our specific solution to this problem

Problem Statement: The decentralized finance (DeFi) industry and other emerging sectors generate vast amounts of social data across various platforms. This data is often fragmented and lacks coherent structure, making it challenging to derive meaningful insights. Companies struggle to understand community sentiment, engagement trends, and the impact of key influencers. Without a comprehensive tool to consolidate and analyze this data, organizations miss out on opportunities for strategic partnerships, market positioning, and community engagement.

Critical Mass offers a comprehensive knowledge base that analyzes and correlates narratives, engagement levels, reactions, intersections, messaging, and activities across various segments, particularly in industries like DeFi. MediaBubbles integrates social public data from multiple sources into a robust Knowledge Layer. This layer serves as an interface for users to access insights, conduct research, and understand dependencies in social data, facilitating informed decision-making and strategic planning. 

MediaBubbles is a platform designed to explore the Critical Mass around narratives. It allows users to:
  - Identify intersections between your projects and others to discover potential partnerships.
  - Analyze active sentiment within your audience based on their activities, visualized through a Social Media Graph. 

Project details

- Audience Analysis: MediaBubbles monitors public social media data, analyzing discussions in groups and intersections with competing products. This analysis reveals opportunities for new income streams and partnerships, helping you connect with diverse audience needs.
- Sentiment and Critical Mass: The platform transforms public discourse into a narrative pulse, shedding light on market trends and identifying key products. This helps understand the importance and impact of various products in the market.
- Product Development: For open-source projects, MediaBubbles tracks commit speeds, technology stacks, and active contributors, comparing them against market capitalizations. This allows you to match narratives with the success of building and maintaining large followings and ongoing development efforts.

Existing resources

- Do we have existing resources to leverage for this project? Yes
- Description of existing resources: MediaBubbles has a robust infrastructure, including:
  - Professional Competence and Soft Skills: A highly skilled team with expertise in AI, data management, and sentiment analysis.
  - Hardware: High-performance servers for data computation and storage.
  - Software:
    - Data consolidation services to aggregate data from various sources.
    - A data lake for centralized storage and management.
    - APIs for seamless data access and integration.
    - A front-end interface for user interaction and data visualization.

Open Source Licensing

Custom

- License: Custom (based on MIT License)
- Describe license details and, if applicable, list any components that are not subject to this license: The MediaBubbles platform license model is based on the MIT License, providing APIs with free calls for fundamental research on Social Sentiment and Narrative, utilizing Knowledge Graph infrastructure components. Any proprietary algorithms or data sources used within the platform are not subject to this open-source license.

Additional links

Product pitch Deck

Additional videos

Testing of Visuals for User

Proposal Video

Placeholder for Spotlight Day Pitch-presentations. Video's will be added by the DF team when available.

  • Total Milestones

    3

  • Total Budget

    $120,000 USD

  • Last Updated

    20 May 2024

Milestone 1 - Initial KG Deployment and Integration GitHub

Description

. Activity and Updates: - Track the activity and frequency of updates in the codebase. . Community Involvement: - Monitor community involvement in development and enhancements.

Deliverables

. Initial Knowledge Graph Deployment: - Deploy a functional Knowledge Graph representing all Deep Funding content. - Ensure the Knowledge Graph is structured for scalability and future ecosystem-wide integration. . Data Ingestion: - Implement the ability to ingest data from the main portal via an API provided by Deep Funding. - Integrate additional data source (Github) and store the data in the Knowledge Graph. . Documentation: - Provide comprehensive documentation detailing the Knowledge Graph's structure and functionality. - Ensure the documentation enables other teams to work with and build upon the Knowledge Graph.

Budget

$35,000 USD

Milestone 2 - Initial KG Deployment and Integration - Telegram

Description

Market Trends and Sentiments - Analyze general trends and sentiments within the communities. - Monitor reactions to significant news and events. . Popularity and Engagement - Measure user engagement levels in discussions across different platforms. - Track changes in the popularity of projects and tokens over time. . Network Effects - Identify intersections between communities and overall activity among various projects. - Assess the influence of key community members on opinions and decisions.

Deliverables

Initial Knowledge Graph Deployment: - Deploy a functional Knowledge Graph representing all Deep Funding content. - Ensure the Knowledge Graph is structured for scalability and future ecosystem-wide integration. . Data Ingestion: - Implement the ability to ingest data from the main portal via an API provided by Deep Funding. - Integrate additional data source (Telegram) and store the data in the Knowledge Graph. . Documentation: - Provide comprehensive documentation detailing the Knowledge Graph's structure and functionality. - Ensure the documentation enables other teams to work with and build upon the Knowledge Graph.

Budget

$40,000 USD

Milestone 3 - Initial KG Deployment and Integration - WarpCast

Description

Market Trends and Sentiments - Analyze general trends and sentiments within the communities. - Monitor reactions to significant news and events. . Popularity and Engagement - Measure user engagement levels in discussions across different platforms. - Track changes in the popularity of projects and tokens over time. . Network Effects - Identify intersections between communities and overall activity among various projects. - Assess the influence of key community members on opinions and decisions.

Deliverables

Initial Knowledge Graph Deployment: - Deploy a functional Knowledge Graph representing all Deep Funding content. - Ensure the Knowledge Graph is structured for scalability and future ecosystem-wide integration. . Data Ingestion: - Implement the ability to ingest data from the main portal via an API provided by Deep Funding. - Integrate additional data source (Warpcast) and store the data in the Knowledge Graph. . Documentation: - Provide comprehensive documentation detailing the Knowledge Graph's structure and functionality. - Ensure the documentation enables other teams to work with and build upon the Knowledge Graph.

Budget

$45,000 USD

Join the Discussion (7)

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7 Comments
  • 0
    commentator-avatar
    CLEMENT
    Jun 2, 2024 | 10:10 AM

    Hey Alex. Great job with this. I want to also draw your attention to the fact that addressing biases in data sources and analysis are essential considerations for maintaining the integrity and trustworthiness of the platform that maybarise from this RFP ? Any measures to check this ?

    • 0
      commentator-avatar
      Alex Blagirev
      Jun 6, 2024 | 10:19 AM

      Hey Clement, thank you for your feedback. I really appreciate it. We track users' activity, and there are some adjustments, but in general, our task is to work with factual information without adjusting it or doing special corrections. Therefore, the reliability of the source doesn't need to be checked since the source speaks the information about itself.   

      • 0
        commentator-avatar
        CLEMENT
        Jun 8, 2024 | 12:13 PM

        Thanks for the clarification. I really appreciate. Thanks

  • 0
    commentator-avatar
    Victor
    May 20, 2024 | 6:17 AM

    Is this proposal compliant with the actual RFP: https://deepfunding.ai/rfp/content-knowledge-graph/ ?

    If not, please add it to another pool such as Miscellaneous or, in case you are utilizing/creating an AI service, to 'new services.'

    • 0
      commentator-avatar
      Alex Blagirev
      May 20, 2024 | 11:11 AM

      Yes, of course it is compliant. The outcomes of this proposal will be:  Initial Knowledge Graph Deployment: A functional KG that represents all Deep Funding content, structured for scalability and future integration across the ecosystem. Data Ingestion: Ability to ingest data from the main portal via an API offered by DF (must have) as well as other sources (nice to have) and to store it in the KG.  Thorough Documentation: provide comprehensive documentation detailing the structure and functionality of the KG to allow other teams to work with and to work on the KG. Collaboration with Application projects: Coordinate with and integrate support for the teams awarded in the Data Applications RFP. This includes making the necessary APIs available for connecting data pipelines to the KG and searching the data in the KG. Maintenance & Hosting Plan: Accompany this with a maintenance plan to ensure ongoing support, hosting, and basic updates for 1 year (included in the maximum award). Integration with SingularityNET's AI platform as a 'knowledge node': A minimum of 10% of the budget is suggested to be reserved for this purpose.

      • 0
        commentator-avatar
        Alex Blagirev
        May 20, 2024 | 11:12 AM

        Let me know if you see that any attributes of the proposal need to be adjusted

      • 0
        commentator-avatar
        Alex Blagirev
        May 20, 2024 | 11:29 AM

        The Critical Mass DB already consolidates data for Telegram / GitHub (gives unique insights already), so we will add Knowledge Graphs, Launch Knowledge Nodes (Ocean / other knowledge nodes providers), and integrate it with the SingularityNET AI marketplace and ICP blockchain, which has been preliminary discussed with the ICP team so far. Brief UI video -> https://www.youtube.com/watch?v=IVI6cReb9i8

Reviews & Rating

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5 ratings
  • 0
    user-icon
    Ayo OluAyoola
    Jun 10, 2024 | 4:01 AM

    Overall

    4

    • Feasibility 3
    • Viability 3
    • Desirabilty 5
    • Usefulness 4
    MediaBubbles: Analyzing Social Buzz

    This platform helps businesses understand social media conversations (DeFi etc.) by analyzing narratives, engagement, and activity.

    Promising, but needs work on:

    • Data access: How will MediaBubbles get social media data (APIs, legalities)?
    • Data handling: Can it manage large data volumes and complex analysis?
    • Standing out: What makes MediaBubbles unique compared to existing tools?
    • Making money: How will MediaBubbles generate revenue (subscriptions etc.)?

    Strengths:

    • Analyzes social media narratives, engagement, and activity.
    • Offers audience analysis, sentiment tracking, and partnership identification.
    • Leverages existing tech for data collection and visualization.

    Overall, MediaBubbles has potential, but needs a clearer plan on data, competition, and business model.

     

    I hope you get funded. We can partner.
    Please do check us out at  MarketIn API. We are developing the first-ever Marketing API that you can integrate into your solution at no cost, helping you achieve widespread user adoption.

    You are about to create a great solution, you must ensure the world knows about it, we want to help you do that. Our API is designed to help you reach the critical mass needed for successful adoption.

    https://deepfunding.ai/proposal/marketing-api-by-an-agi/  

     

    And if you are looking for one of the most novel ideation projects in this round of funding. Please do drop a review or comment, and please do plan to vote for us; we would like to explore just how much AI can do for us in terms of our soft needs of one another.
    Check Ghost AI here

    https://deepfunding.ai/proposal/persona-ai/

  • 0
    user-icon
    Max1524
    Jun 10, 2024 | 7:15 AM

    Overall

    4

    • Feasibility 4
    • Viability 4
    • Desirabilty 4
    • Usefulness 4
    Kudos team for know how take advantage technology

    Kudos to the team for knowing how to take advantage of technology

    The strongest point of this proposal is the data collection and visualization. I realized this when I learned that the team mentioned taking advantage of advanced technology, that is, knowing how to distill the good things to take advantage of to create their products. This is commendable.

  • 0
    user-icon
    CLEMENT
    Jun 2, 2024 | 10:14 AM

    Overall

    4

    • Feasibility 4
    • Viability 4
    • Desirabilty 4
    • Usefulness 4
    This will facilitate research of social dynamics

    I would foremostly comment that MediaBubbles presents an innovative approach to aggregating social public data from various sources and placing it on the Knowledge Layer. It seeks to achieve this by providing an interface for users to access and analyze this data, the platform aims to facilitate research and understanding of social dynamics and dependencies.

    I will also like to add that from a general perspective, MediaBubbles has the potential to impact how individuals and organizations interact with and understand social data. Also, it is capable of contributing to the SNET AI Marketplace, because it will by offer a unique resource for accessing and analyzing social data.

    Kudos to the team !

  • 0
    user-icon
    Tu Nguyen
    Jun 3, 2024 | 7:36 AM

    Overall

    4

    • Feasibility 4
    • Viability 5
    • Desirabilty 4
    • Usefulness 5
    Social Critical Mass Graph

    The problem this proposal will solve is that data is often fragmented and lacks a coherent structure, making it difficult to draw meaningful insights in the decentralized finance industry and other sectors. other emerging. The solution of this proposal is that they will provide a comprehensive knowledge base to analyze and correlate stories, engagement, reactions, intersections, messages and activities across multiple segments differently, especially in industries like DeFi.
    This is a good project. They have members with a lot of experience and skills. I only have 1 opinion. They should clearly define the start and end times of milestones.

  • -2
    user-icon
    Joseph Gastoni
    May 22, 2024 | 12:58 PM

    Overall

    4

    • Feasibility 4
    • Viability 3
    • Desirabilty 3
    • Usefulness 4
    platform (MediaBubbles) for analyzing social data.

    This proposal outlines a platform (MediaBubbles) for analyzing social data (Critical Mass) related to narratives, engagement, and activities in various sectors like DeFi. Here's a breakdown of its strengths and weaknesses:

    Feasibility:

    • Moderate-High: Data acquisition from social media platforms might require API access and handling large data volumes could be challenging.
      • Strengths: The core functionalities (data collection, analysis, visualization) leverage existing technologies.
      • Weaknesses: The proposal lacks details on data acquisition strategies (API access, legalities) and data processing capabilities.

    Viability:

    • Moderate: Success depends on efficient data collection, accurate analysis, user adoption, and the platform's ability to provide valuable insights compared to existing solutions.
      • Strengths: The proposal addresses a need for structured social data analysis in sectors like DeFi.
      • Weaknesses: The proposal lacks details on the business model and how it will compete with established social listening tools.

    Desirability:

    • Moderate-High: For companies seeking insights into social data for market research, audience analysis, and strategic planning, this could be desirable.
      • Strengths: The proposal emphasizes uncovering hidden connections, sentiment analysis, and identifying key narratives.
      • Weaknesses: The proposal needs to demonstrate the platform's unique value proposition compared to existing social listening and market research tools.

    Usefulness:

    • Moderate-High: The project has the potential to improve companies' understanding of social data, but its impact depends on the accuracy and depth of the insights provided.
      • Strengths: The proposal offers functionalities like audience analysis, sentiment tracking, and identifying potential partnerships.
      • Weaknesses: The proposal lacks details on how the platform will handle potential biases in social media data and the evolving nature of online discourse.

    Overall, the Critical Mass (MediaBubbles) project has a promising approach, but focus on:

    • Data Acquisition Strategy: Clearly outlining the plan for accessing social media data, including API integrations and handling data privacy regulations.
    • Data Processing Capabilities: Specifying the platform's infrastructure for handling large data volumes and performing complex social data analysis.
    • Competitive Advantage: Demonstrating how MediaBubbles offers unique insights or functionalities compared to existing social listening tools.
    • Business Model: Defining a clear business model for monetizing the platform and ensuring its long-term sustainability.

    Strengths:

    • Focuses on analyzing social data narratives, engagement, and activities.
    • Offers functionalities for audience analysis, sentiment tracking, and identifying partnerships.
    • Leverages existing technologies for data collection and visualization.

    Weaknesses:

    • Lacks details on data acquisition strategy, data processing capabilities, and competitive advantage.
    • Needs a clear business model for long-term sustainability.

    user-icon
    Alex Blagirev
    May 24, 2024 | 5:33 PM
    Project Owner

    Thank you so much for your review 


    ### Response to Feasibility and Viability Concerns

    Feasibility:

    Moderate-High: Data acquisition from social media platforms indeed requires careful handling of API access and large data volumes. Here is a detailed explanation of our approach:

    1. Data Acquisition Strategy:
       - We will use official APIs provided by major social media platforms such as Twitter, Facebook, LinkedIn, and Telegram. This ensures compliance with data usage policies and regulations.
       - We have a dedicated team to manage API rate limits and optimize data retrieval processes to handle large data volumes efficiently.

    2. Data Processing Capabilities:
       - Our platform will leverage scalable cloud infrastructure (e.g., AWS, Google Cloud) to process and store the acquired data.
       - We will use distributed computing frameworks like Apache Spark for real-time data processing and analysis.
       - To ensure data security and privacy, we will implement robust encryption methods and adhere to GDPR and other relevant data protection regulations.

    Strengths: The core functionalities, such as data collection, analysis, and visualization, are built on well-established technologies that have proven scalability and reliability.

    Weaknesses: The proposal can be enhanced by detailing the data acquisition strategies and legal considerations more explicitly.

    Viability:

    Moderate: The success of the platform hinges on efficient data collection, accurate analysis, user adoption, and providing unique insights that stand out from existing solutions.

    1. Competitive Advantage:
       - MediaBubbles offers unique functionalities such as identifying hidden connections and providing deep sentiment analysis that existing social listening tools may not offer.
       - By integrating Knowledge Graphs (using Atomspace and Knowledge Nodes), our platform can provide more granular and interconnected insights, enhancing the value of the data analysis.

    2. Business Model:
       - We will adopt a subscription-based model for businesses, offering tiered pricing based on the volume of data processed and the features accessed.
       - Additionally, we plan to offer premium services for custom data analysis and insights generation.

    Strengths: The proposal meets a critical need for structured social data analysis in sectors like DeFi.

    Weaknesses: Further details on the business model and competitive landscape would strengthen the proposal.

    Desirability:

    Moderate-High: Companies that need insights into social data for market research, audience analysis, and strategic planning will find this platform highly desirable.

    1. Unique Value Proposition:
       - MediaBubbles emphasizes uncovering hidden connections, sentiment analysis, and key narrative identification, providing a competitive edge over other tools.
       - Our use of decentralized components through technologies like NuNet will enhance data security and user trust.

    Weaknesses: The proposal should demonstrate how our platform offers a unique value proposition compared to existing solutions.

    Usefulness:

    Moderate-High: The project can significantly enhance companies' understanding of social data, contingent on the accuracy and depth of insights provided.

    1. Handling Biases and Evolving Nature of Data:
       - We will implement machine learning models that continuously learn and adapt to the evolving nature of online discourse.
       - Regular audits and updates to our algorithms will help minimize biases in social media data.

    Strengths: The functionalities like audience analysis, sentiment tracking, and partnership identification are crucial for strategic decision-making.

    Weaknesses: Additional details on managing data biases and ensuring the relevance of insights are necessary.

    Владимир, [24/05/24 16.14]
    Decentralized Approach with Masternodes:

    To address concerns about centralized data processing and to align with the expectations of distributed and scalable solutions on the blockchain, we propose the following decentralized approach:

    1. Masternodes:
       - Masternodes will act as decentralized servers capable of performing centralized computations while being operated by independent participants. These nodes will handle data collection, processing, and storage in a distributed manner.
       - Participants operating masternodes will be rewarded through a token distribution mechanism, incentivizing the maintenance and operation of these nodes.

    2. Integration with SingularityNET and NuNet:
       - By leveraging SingularityNET's decentralized AI network and NuNet's decentralized computing resources, we can create a more resilient and scalable infrastructure.
       - This approach ensures that data collection and processing are not only decentralized but also compliant with blockchain principles, providing better security and trust.

    References to Similar Projects:
    - Horizen: A blockchain platform that utilizes masternodes to enhance its privacy features and scalability.
    - Dash: Known for its masternode network which supports its InstantSend and PrivateSend functionalities.

    By addressing these areas, we can enhance the feasibility, viability, desirability, and usefulness of the Critical Mass (MediaBubbles) project while ensuring compliance with decentralized computing standards and blockchain principles.

Summary

Overall Community

4

from 5 reviews
  • 5
    0
  • 4
    5
  • 3
    0
  • 2
    0
  • 1
    0

Feasibility

3.8

from 5 reviews

Viability

3.8

from 5 reviews

Desirabilty

4

from 5 reviews

Usefulness

4.2

from 5 reviews

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