Apply VADER or BERT for sentiment scoring, or use K-Means clustering for thematic grouping. 4. Structuring the Paper
Use Python (Pandas) to select specific languages or date ranges. 3. Methodology twitter 5.mil.zip
"Do high-frequency news posts correlate with rapid stock market movement?" 2. Data Processing (The '.zip' File) Extraction: Unzip the data. Apply VADER or BERT for sentiment scoring, or
Remove null values, URLs, special characters, and emojis. Remove null values, URLs, special characters, and emojis
"How can we identify automated, malicious bot traffic in high-volume datasets?"
"What is the sentiment trend regarding [Topic] over the last 5 years?"
[e.g., Sentiment Analysis of 5 Million Tweets Regarding... ] Abstract: Summary of the findings. Introduction: Why analyze this data? Data & Methods: How was the data cleaned and analyzed? Results: Graphs, charts, and key statistics. Discussion/Conclusion: What do the results mean? To help you further, could you specify: