What is Sentigraph?
Sentigraph is a system that provides predictive insights aimed at improving future events based on emotion data obtained by analyzing users’ reactions in a given event leveraging Artificial Intelligence and blockchain. A suitable use case is analyzing twitter hashtags using IBM’s Watson and an algorithm to compute the graph index, gi. The system can analyze equity markets, various review systems, social media, politics, healthcare, precog, and security via related twitter hashtags.
How will EMOT be used?
EMOT will be used to compute the graph index of events (first use case is Twitter hashtags).
EMOT will also be used for the EVP game, which will incentivize users to predict the sentiment direction of twitter hashtags.
What is expected from Sentigraph in the short & long term?
Short term: The platform will offer useful predictive insights based on the computed graph indexes on all Twitter hashtags, while illustrating the performance of those hashtags with regards to their corresponding sentiments
Long term: Sentigraph will scale beyond Twitter and incorporate various social networks (e.g. Instagram, Facebook etc.), news media, sports betting, national security, equity markets, politics, transportation, crime prediction/prevention, gene expression research, and various other use cases.
- Verifiable team with good networks and plenty of former colleague and client endorsements. Team skills have heavy focus on business development and investor relations
- The total initial valuation of $20M is reasonable for such a big potential business case with a reliable team and solid vision
- The utility token model works well for this kind of service
- The relatively complex information processing model is well compressed into an understandable business proposal
- The White Paper provides interesting details about the backend process of the easy-to-use tool
- Partnership with a blockchain marketing company with a good portfolio and testimonials
- The project has pretty good community outreach for such a young project
- The project has quite plenty of industry analysis endorsements
- All the provided material summarize the idea, purpose and token economics in a clear way, pretty easy to find the relevant details
- The team could have more product development members
- The graphic part of the project could use refining
- The alpha release gives a vague idea about the service, but does not yet explain in detail what the given rate indicates
- Roadmap looks realistic, except some of the goals such as establishing a university within a year. This seems like bit of a hasty plan considering the core product is not yet ready or spread on the global markets
- The great goal to partner with Twitter and IBM sounds good but is yet left to be proven successful