This project involves building a machine learning model to analyze the sentiment of social media posts. The model will classify posts as positive, negative, or neutral based on their content. This project can help businesses understand public opinion about their products or services by analyzing user feedback on social media platforms.

 

Steps to Implement:

Data Collection:

• Use APIs from social media platforms like Twitter, Facebook, or Instagram to collect posts related to specific keywords or hashtags.
• Alternatively, use pre-collected datasets from sources like Kaggle.

Data Preprocessing:

• Clean the text data by removing URLs, special characters, and stop words.
• Tokenize the text and convert it to lowercase.
• Perform stemming or lemmatization to reduce words to their base forms.

Exploratory Data Analysis (EDA):

• Visualize the distribution of sentiments in the dataset.
• Analyze the most common words in positive, negative, and neutral posts.

Feature Engineering:

• Convert the text data into numerical features using techniques like TF-IDF or word embeddings (Word2Vec, GloVe, BERT).

Model Building:

• Split the dataset into training and testing sets.
• Choose a suitable machine learning model such as Logistic Regression, Naive Bayes, or a deep learning model like LSTM or BERT.
• Train the model on the training set and evaluate its performance on the testing set.

Model Evaluation:

• Use metrics like accuracy, precision, recall, and F1-score to evaluate the model.
• Perform cross-validation to ensure the model generalizes well to unseen data.

Deployment:

• Create a web application using Flask or FastAPI to input new social media posts and get sentiment predictions.
• Deploy the model and web application on a cloud platform like Heroku, AWS, or Vercel.

Documentation and Reporting:

• Document the project steps, methodologies, and findings.
• Create visualizations and reports to present the results.

For this project you can use any Tech stack that you comfortable with, as long as you are achieving the goal. happy coding!!

author: Anita