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Python Social Media Analytics

You're reading from Python Social Media Analytics Analyze and visualize data from Twitter, YouTube, GitHub, and more

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781787121485

Length 312 pages

Edition 1st Edition

Languages

Python

Tools

GitHub

Concepts

Data Analysis

Authors (3):

Baihaqi Siregar

Siddhartha Chatterjee

Michal Krystyanczuk

View More author details

Table of Contents (10) Chapters

Preface

1. Introduction to the Latest Social Media Landscape and Importance

2. Harnessing Social Data - Connecting, Capturing, and Cleaning FREE CHAPTER

3. Uncovering Brand Activity, Popularity, and Emotions on Facebook

4. Analyzing Twitter Using Sentiment Analysis and Entity Recognition

5. Campaigns and Consumer Reaction Analytics on YouTube – Structured and Unstructured

6. The Next Great Technology – Trends Mining on GitHub

7. Scraping and Extracting Conversational Topics on Internet Forums

8. Demystifying Pinterest through Network Analysis of Users Interests

9. Social Data Analytics at Scale – Spark and Amazon Web Services

Scope and process

GitHub API allows us to get information about public code repositories submitted by users. It covers lots of open-source, educational and personal projects. Our focus is to find the trending technologies and programming languages of last few months, and compare with repositories from past years. We will collect all the meta information about the repositories,

Name: The name of the repository
Description: A description of the repository
Watchers: People following the repository and getting notified about its activity
Forks: Users cloning the repository to their own accounts
Open Issues: Issues submitted about the repository

We will use this data, a combination of qualitative and quantitative information, to identify the most recent trends and weak signals. The process can be represented by the steps shown in the following figure:

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Authors (3)

Siddhartha Chatterjee

Siddhartha Chatterjee

Siddhartha Chatterjee is an experienced data scientist with a strong focus in the area of machine learning and big data applied to digital (e-commerce and CRM) and social media analytics. He worked between 2007 to 2012 with companies such as IBM, Cognizant Technologies, and Technicolor Research and Innovation. He completed a Pan-European Masters in Data Mining and Knowledge Management at Ecole Polytechnique of the University of Nantes and University of Eastern Piedmont, Italy. Since 2012, he has worked at OgilvyOne Worldwide, a leading global customer engagement agency in Paris, as a lead data scientist and set up the social media analytics and predictive analytics offering. From 2014 to 2016, he was a senior data scientist and head of semantic data of Publicis, France. During his time at Ogilvy and Publicis, he worked on international projects for brands such as Nestle, AXA, BNP Paribas, McDonald's, Orange, Netflix, and others. Currently, Siddhartha is serving as head of data and analytics of Groupe Aéroport des Paris.

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Baihaqi Siregar

Baihaqi Siregar

See other products by Baihaqi Siregar

Michal Krystyanczuk

Michal Krystyanczuk

Michal Krystyanczuk is the co-founder of The Data Strategy, a start-up company based in Paris that builds artificial intelligence technologies to provide consumer insights from unstructured data. Previously, he worked as a data scientist in the financial sector using machine learning and big data techniques for tasks such as pattern recognition on financial markets, credit scoring, and hedging strategies optimization. He specializes in social media analysis for brands using advanced natural language processing and machine learning algorithms. He has managed semantic data projects for global brands, such as Mulberry, BNP Paribas, Groupe SEB, Publicis, Chipotle, and others. He is an enthusiast of cognitive computing and information retrieval from different types of data, such as text, image, and video.

See other products by Michal Krystyanczuk

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