GitHub - mananabbasi/Dissertation-: This project analyzes the impact of Twitter sentiment on Bitcoin prices using NLP, sentiment analysis, and topic modeling (LDA). Tweets are clustered by sentiment and integrated with Bitcoin price data to assess correlations. Random Forest and XGBoost models are built to predict Bitcoin price trends based on sentiment and market data.

Name		Name	Last commit message	Last commit date
52_Influencer_Users_on_Cryptocurrency_(Feb_2021_–_Jun_2023)_Tweet_Dataset.ipynb		52_Influencer_Users_on_Cryptocurrency_(Feb_2021_–_Jun_2023)_Tweet_Dataset.ipynb
Analyzing_Bitcoin_Price_Data_(Minute_by_Minute)_and_Capturing_the_Trends_from_2012_till_2025.ipynb		Analyzing_Bitcoin_Price_Data_(Minute_by_Minute)_and_Capturing_the_Trends_from_2012_till_2025.ipynb
Combined_Analysis_of_Twitter_Sentiment_and_Bitcoin_Market_Data.ipynb		Combined_Analysis_of_Twitter_Sentiment_and_Bitcoin_Market_Data.ipynb
Cryptocurrency_Trends_and_Global_Adoption_.ipynb		Cryptocurrency_Trends_and_Global_Adoption_.ipynb
Dataset,md		Dataset,md
Social_Media_Sentiment_and_Behavioral_Insights_Analyzing_Bitcoin_Tweets_(2021–2023).ipynb		Social_Media_Sentiment_and_Behavioral_Insights_Analyzing_Bitcoin_Tweets_(2021–2023).ipynb
fixed_Predictive_Modeling_Using_Combined_Sentiment_and_Bitcoin_Price_Data.ipynb		fixed_Predictive_Modeling_Using_Combined_Sentiment_and_Bitcoin_Price_Data.ipynb

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This project analyzes the impact of Twitter sentiment on Bitcoin prices using NLP, sentiment analysis, and topic modeling (LDA). Tweets are clustered by sentiment and integrated with Bitcoin price data to assess correlations. Random Forest and XGBoost models are built to predict Bitcoin price trends based on sentiment and market data.

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