Cryptocurrency tweet web application development -- 2
Budget: $15 – $25 USD
Social media engagement and cryptocurrency peformance web application.
Please see doc attached
Somethings to keep in mind before starting:
1. The twitter API has been integrated and we can search recent tweets by querying using an input component and the results are rendered in a table. The thing I’m concerned about is the search function being open. We want to find the newer coins that have the best chance of success given engagement around them. So, the code should be optimized in such a way that we get only crypto tweets from the search and not just some random tweets.
2. Engagement coefficient needs to be calculated for which the code will be provided to you.
3. Sentiment analysis is already done.
4. The botometer api may be deprecated now as twitter api has changed. I’m thinking botsentinel could be utilized though. https://botsentinel.com
5. Basically, what we want is to discern organic fervour and growth of accounts around the coins we are detecting from spam bots that are deployed for a pump and dump scheme. Going back again to the paper I sent, we want the engagement coefficient to be clean of bot activity as much as possible. And to display these factors in the dashboard with clear indications of “safe” vs. “fraudulent” coins.
6. Basic line charts for historical price data are already implemented.
7. For long term and short-term prediction, use Llama3: https://ollama.com/library/llama3:8b
Please see doc attached
Somethings to keep in mind before starting:
1. The twitter API has been integrated and we can search recent tweets by querying using an input component and the results are rendered in a table. The thing I’m concerned about is the search function being open. We want to find the newer coins that have the best chance of success given engagement around them. So, the code should be optimized in such a way that we get only crypto tweets from the search and not just some random tweets.
2. Engagement coefficient needs to be calculated for which the code will be provided to you.
3. Sentiment analysis is already done.
4. The botometer api may be deprecated now as twitter api has changed. I’m thinking botsentinel could be utilized though. https://botsentinel.com
5. Basically, what we want is to discern organic fervour and growth of accounts around the coins we are detecting from spam bots that are deployed for a pump and dump scheme. Going back again to the paper I sent, we want the engagement coefficient to be clean of bot activity as much as possible. And to display these factors in the dashboard with clear indications of “safe” vs. “fraudulent” coins.
6. Basic line charts for historical price data are already implemented.
7. For long term and short-term prediction, use Llama3: https://ollama.com/library/llama3:8b