Ramadan Social Media Analysis image Ramadan Social Media Analysis image Ramadan Social Media Analysis image

Ramadan Social Media Analysis

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In this project, we explore and analyze various aspects of Moroccan society and culture during the Ramadan month from social media comments.

Features

  • Data Collection : Gather data from multiple social media platforms.
  • Text Preprocessing : Clean, normalize, and prepare textual data for analysis.
  • Sentiment Analysis : Determine the prevailing trends and emotions expressed in the data.
  • Results Visualization : Present findings using informative charts and tables.

Overview

The project aims to analyze sentiments expressed on social media during the month of Ramadan to understand user trends, opinions, and emotions during this significant period. It involves collecting data from various platforms such as Twitter, Facebook, Instagram, Hespress, and YouTube using APIs or web scraping techniques. The collected data will be preprocessed by cleaning it to remove duplicates, special characters, and URLs, followed by text normalization, including converting to lowercase, tokenizing, removing stop words, and lemmatization or stemming. Sentiment analysis will then classify the texts into categories like positive, negative, or neutral, potentially using advanced models like BERT or RoBERTa for a detailed emotional analysis. Finally, the results will be visualized through graphs and charts to illustrate sentiment trends over time, complemented by informative tables summarizing the descriptive statistics and key findings.

Tools

  • Tweepy : For extracting data from Twitter.
  • Youtube API : For extracting comments from YouTube.
  • Facebook Graph API : For collecting data from Facebook.
  • BeautifulSoup, Scrapy : For web scraping data from sources like Hespress.
  • NLTK, SpaCy : For natural language processing tasks.
  • Regex : For manipulating and cleaning textual data.
  • Matplotlib, Seaborn : For creating charts and graphs.