/TokenSentiment

OCEAN Token Sentiment Analysis Challenge

Primary LanguageJupyter Notebook

TokenSentiment

OCEAN Token Sentiment Analysis Challenge

Presentatation in doc folder !

Introducing the OCEAN Token Sentiment Data Challenge! We're calling on data scientists, analysts, and data engineers to participate in this exciting competition. The challenge revolves around developing data analysis reports and machine learning models that accurately assess investor sentiment towards the OCEAN token.

Social media, particularly Twitter, has emerged as a valuable source of information and opinions about cryptocurrencies. Investors express their perspectives, analysis, and emotions through tweets, creating a continuous flow of market-related data. By analyzing this data, we can identify trends and shifts in sentiment that can significantly impact the token's value and popularity. This analysis plays a vital role in helping investors manage their investments and make well-informed decisions in response to market fluctuations.

Data Analysis
Based on the data in the provided datasets, address the following questions:

  • Calculate the correlation between the price of $OCEAN and the number of tweets containing "$OCEAN". What conclusions can be drawn from this correlation?
  • Determine the correlation between the price of $OCEAN and the number of likes received by tweets containing "$OCEAN". What insights can be derived from this correlation?
  • Establish the correlation between the price of $OCEAN and the number of retweets generated by tweets containing "$OCEAN". What conclusions can be made from this correlation?
  • Assess the correlation between the price of $OCEAN and the number of individuals tweeting with the cashtag "$OCEAN". What conclusions can be drawn from this correlation?
  • Analyze the impact of influential tweets on the price of the OCEAN token. What conclusions can be drawn from this analysis?

Prediction Model (30 points):

  • Develop a machine learning model capable of classifying tweets as bullish, bearish, or neutral. You have the freedom to use any dataset for this task.

  • Apply this model to tweets containing $OCEAN and observe how investor sentiment towards the token evolves. Is there a correlation between investor sentiment and the token's price?

Report
Submit a comprehensive report detailing the findings mentioned above. Ensure that your report incorporates both qualitative and quantitative insights. The evaluation of reports will consider factors such as presentation structure, approach, content, and completeness.

DATA SOURCES :