Reuter-News-Data-Analysis

This project involves processing Reuters news data, performing sentiment analysis on news titles, and storing the results in a MongoDB database.

Problem 1: Reuters News Data Reading & Transformation and Storing in MongoDB

Objective: To read news articles from provided files, extract relevant information, and store them in a MongoDB database.

1. Data Processing:

   • A Java program (ReutRead.java) to scan the required text between <TITLE></TITLE> and tags within each tag.
   • Extract the title and body of each news article.

2. Storing in MongoDB:

   • Creating a MongoDB database named ReuterDb.
   • Storing each news article as a document in the database.
   • Each document should contain fields for title and body, structured as follows:

    {
  "title": "ADVANCED MAGNETICS ADMG IN AGREEMENT",
  "body": "Advanced Magnetics Inc said it reached a four mln dlrs research and development agreement with…"
    }

Problem 2: Sentiment Analysis using Bag-of-Words Model on Reuters News Titles

Objective: Performing sentiment analysis on news article titles using a Bag-of-Words (BOW) model.

1. Bag-of-Words Creation: Implemented a Java program to create a bag-of-words for each news title.

2. Comparison with Positive and Negative Words:

   • Downloaded the lists of positive and negative words from online sources.
   • Compared each word in the bag-of-words with the lists of positive and negative words.
   • Performed word-by-word comparison to determine sentiment.

3. Tagging News Titles:

   • Tagged each news title as "positive", "negative", or "neutral" based on the overall score.
   • Inserted the titles and performed automatic matching with score detection using the program.
   • Structured the output in a tabular format for presentation.