Mastering Social Media Mining with Python by Marco Bonzanini

By Marco Bonzanini

Acquire and research information from all corners of the social internet with Python

About This Book

  • Make experience of hugely unstructured social media info with assistance from the insightful use situations supplied during this guide
  • Use this easy-to-follow, step by step consultant to use analytics to advanced and messy social data
  • This is your one-stop option to fetching, storing, examining, and visualizing social media data

Who This e-book Is For

This ebook is for intermediate Python builders who are looking to interact with using public APIs to assemble facts from social media structures and practice statistical research so one can produce worthwhile insights from facts. The e-book assumes a easy figuring out of the Python average Library and gives useful examples to lead you towards the construction of your information research undertaking in keeping with social data.

What you are going to Learn

  • Interact with a social media platform through their public API with Python
  • Store social information in a handy layout for facts analysis
  • Slice and cube social facts utilizing Python instruments for information science
  • Apply textual content analytics suggestions to appreciate what individuals are conversing approximately on social media
  • Apply complex statistical and analytical suggestions to provide precious insights from data
  • Build appealing visualizations with net applied sciences to discover information and current facts products

In Detail

Python is the programming language of selection for information scientists to prototype, visualize, and run facts analyses on small- and medium-sized information units. numerous companies are turning to Python to resolve the issues of figuring out purchaser habit and turning uncooked facts into actionable buyer insights.

This e-book may help to procure and learn facts from major social media websites. it's going to enable you hire clinical Python instruments to mine well known social web pages equivalent to fb, Twitter, Quora, and more.

We will discover the Python libraries and canopy each one point of social media mining. we'll educate you to boost info mining instruments that use a social media API and the way to create your personal info research initiatives utilizing Python.

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If you're new to Python, have some time for the bigger download and disk space to spare, and don't want to install all the packages manually, you can get started with Anaconda. For Windows and macOS, Anaconda is available with either a graphical or command-line installer. 5 shows a screen capture of the installation procedure on a macOS. For Linux, only the command-line installer is available. In all cases, it's possible to choose between Python 2 and Python 3. 4 # or favorite version The environment can be activated with the following command: $ conda activate my_env Similar to what happens with virtualenv, the environment name will be visible in the prompt: (my_env)$ New packages can be installed for this environment with the following command: $ conda install [package-name] Finally, you can deactivate an environment by typing the following command: $ conda deactivate Another nice feature of conda is the ability to install packages from pip as well, so if a particular library is not available via conda install, or it's not been updated to the latest version we need, we can always fall back to the traditional Python package manager while using a conda environment.

There are mainly two distributions that ship with conda: the batteries-included version, Anaconda, which comes with approximately 100 packages for scientific computing already installed, and the lightweight version, Miniconda, which simply comes with Python and the conda installer, without external libraries. If you're new to Python, have some time for the bigger download and disk space to spare, and don't want to install all the packages manually, you can get started with Anaconda. For Windows and macOS, Anaconda is available with either a graphical or command-line installer.

The aim of the process is to answer interesting (and sometimes difficult) questions using data mining techniques to enrich our knowledge about a particular domain. For example, an online retail store can apply data mining to understand how their customers shop. Through this analysis, they are able to recommend products to their customers, depending on their shopping habits (for example, users who buy item A, also buy item B). This, in general, will lead to a better customer experience and satisfaction, which in return can produce better sales.

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