Create README.md

Author: Archi20876

Data Analysis/Sentiment Analysis - Dow Jones (DJIA) Stock using News Headlines/README.md

@@ -0,0 +1,35 @@
+# Sentiment Analysis 😊☹️😑
+
+This project focuses on sentiment analysis, a technique used to determine the emotional tone behind a body of text. By analyzing data from various sources such as social media, customer reviews, and online forums, the project aims to classify text as positive, negative, or neutral. Understanding sentiment can help businesses gauge customer opinions, improve products, and enhance customer satisfaction.
+
+### Objectives :
+
+- Classify Sentiments: Develop models to accurately classify text into categories like positive, negative, and neutral.
+  
+- Understand Customer Feedback: Analyze customer reviews to identify key sentiments associated with products, services, or brands.
+  
+- Monitor Public Opinion: Track sentiment on social media platforms to understand public reactions to events, campaigns, or trends.
+  
+- Improve Decision-Making: Provide actionable insights to businesses, enabling them to make informed decisions based on customer feedback and market sentiment.
+
+### Approach :
+- Data Cleaning & Preprocessing: Clean the data to remove noise (e.g., hashtags, URLs, special characters), and preprocess it by tokenizing, removing stopwords, and lemmatizing the text.
+- Exploratory Data Analysis (EDA):
+Visualize the distribution of sentiments in the dataset.
+Identify common words and phrases associated with positive and negative sentiments.
+Analyze sentiment over time to observe trends.
+  Model Development: Use machine learning algorithms such as Naive Bayes, Multinomial Naive Bayes,Random Forest Classifier , Logistics Regression or deep learning techniques like LSTM to build a sentiment classification model.
+- Sentiment Scoring: Assign sentiment scores to text to quantify the degree of positivity or negativity. 
+- Evaluation & Optimization: Evaluate model performance with precision metrics.
+
+### Applications :
+
+Businesses: Use predictive insights to improve products, services, and customer engagement strategies.
+Marketing Teams: Forecast the success of campaigns and adjust strategies based on predicted trends.
+Social Media Monitoring: Track real-time sentiment and predict future public reactions to events, products, or announcements.
+
+To view the Analysis 👉 [Sentiment Analysis.ipynb](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/Stock%20Sentiment%20Analysis.ipynb)
+
+To view More charts in the Analysis 👉 [Sentiment analysis charts](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/ChartsForBetterUnderstanding.ipynb)
+
+To view the Dataset 👉 [Dataset](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/Stock%20Headlines.csv)