Mining and Analyzing Facebook Data

Use Python, Data Science and Natural Language Processing techniques to extract data and analyze your Facebook page!

Facebook is one of the most popular social networks in the world, which allows you to chat with friends, share messages, links, photos, and videos. Companies can create business pages to promote and sell products and services. On the other hand, users (or fans) can like and follow the pages to receive updates about the company. It is important that companies know how to use the data of this social network in their favor and Facebook provides an API (called Graph API) for extracting several types of information about your page, making it possible to apply Data Science techniques to extract important and interesting insights considering some metrics, such as: engagement, views, content distribution, clicks, and many others!

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What you’ll learn

• Extract data from your Facebook page using the Graph API
• Extract and analyze the following information: basic page data, views, clicks, engagement, impressions, and posts
• Apply natural language processing techniques to analyze your Facebook posts
• Use sentiment analysis to analyze positivity and negativity in user comments
• Aggregate fans by language, city, country, age and gender
• Print various types of graphs to analyze Facebook page information
• Find relationships between page likes and dislikes
• Extract positive and negative actions in your Facebook page
• Compare paid, organic and viral content distribution
• Use time series to predict the future number of page fans using ARIMA algorithm
• Use the Facebook Prophet tool to predict future page engagement
• Extract and analyze the text of posts and the text of comments made by the fans

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