Mining and Analyzing Facebook Data
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
Requirements
- Programming logic
- Basic Python programming
- No Facebook knowledge is required
Description
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! Below you can see the main topics that will be implemented step by step in this course:
Extract data from your Facebook page using the Graph API
Extract and analyze several types of information, such as: basic page data, views, clicks, engagement, impressions and posts
Aggregate page fans by language, city, country, age, and gender
Find relationships between the number of likes and dislikes
View important information about page engagement
View the positive and negative actions of the page's fans
Compare paid, organic and viral content impressions
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 reactions to page posts, such as the number of likes per post
Extract texts from posts and apply natural language processing techniques, such as the word cloud to view the most frequent terms
Perform key-word search in the posts
Extract texts from comments written by the fans of the page to apply sentiment analysis to check whether the comments are positive or negative
During the course, we will use the Python programming language and Google Colab, so it is not necessary to spend time installing softwares on your own machine. You will be able to follow the course with a browser and an Internet connection! This is the best course if this is your first contact with social media data analysis!
Who this course is for:
- Anyone interested in data analysis using social media data
- People interested in applying Artificial Intelligence and Data Science techniques to data extracted from social networks
- People interested in extracting data from social networks
- Undergraduate students who are studying subjects related to Artificial Intelligence, Data Science or Data Analysis
Instructors
![Jones Granatyr](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.7 Instructor Rating
- 32,813 Reviews
- 147,389 Students
- 81 Courses
Olá! Meu nome é Jones Granatyr e já trabalho em torno de 10 anos com Inteligência Artificial (IA), inclusive fiz o meu mestrado e doutorado nessa área. Atualmente sou professor, pesquisador e fundador do portal IA Expert, um site com conteúdo específico sobre Inteligência Artificial. Desde que iniciei na Udemy criei vários cursos sobre diversos assuntos de IA, como por exemplo: Deep Learning, Machine Learning, Data Science, Redes Neurais Artificiais, Algoritmos Genéticos, Detecção e Reconhecimento Facial, Algoritmos de Busca, Mineração de Textos, Buscas em Textos, Mineração de Regras de Associação, Sistemas Especialistas e Sistemas de Recomendação. Os cursos são abordados em diversas linguagens de programação (Python, R e Java) e com várias ferramentas/tecnologias (tensorflow, keras, pandas, sklearn, opencv, dlib, weka, nltk, por exemplo). Meu principal objetivo é desmistificar a área de IA e ajudar profissionais de TI a entenderem como essa tecnologia pode ser utilizada na prática e que possam visualizar novas oportunidades de negócios.
- 4.7 Instructor Rating
- 30,590 Reviews
- 140,153 Students
- 80 Courses
A plataforma IA Expert tem o objetivo de trazer cursos teóricos e práticos de fácil entendimento sobre sobre Inteligência Artificial e Ciência de Dados, para que profissionais de todas as áreas consigam entender e aplicar os benefícios que a IA pode trazer para seus negócios, bem como apresentar todas as oportunidades que essa área pode trazer para profissionais de tecnologia da informação. Também trazemos notícias atualizadas semanais sobre a área em nosso portal.