PRODIGY_DS_04 PRODIGY INFOTECH DATASCIENCE INTERNSHIP TASK-04
Task overview Analyze and visualize sentiment patterns in social media data to understand public opinion and attitudes towards specific topics or brands.
Steps followed in this project Data Collection and Preprocessing:
Understanding Sentiment Data:
Learned how to work with a dataset focused on sentiment analysis, which includes text data (tweets) and sentiment labels (positive, negative, neutral, irrelavant).
Data Cleaning:
Gained experience in preprocessing text data, which involves handling missing values and null values.
Exploratory Data Analysis (EDA):
Data Visualization:
Developed skills in visualizing the distribution of sentiments across different entities or brands using libraries like Matplotlib, Seaborn, or Plotly.
Pattern Recognition:
Identified patterns in the sentiment data, such as trends over time.
Modeling and Evaluation:
Model Building:
Gained experience in building sentiment analysis model
Model Evaluation:
Learned how to evaluate the performance of sentiment analysis models using metrics like accuracy, precision, recall, F1-score.