Python social media analytics: analyze and visualize data from Twitter, YouTube, GitHub, and more
Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book * Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more * Analyze and extract actionable insights from your social data using various Python...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Birmingham ; Mumbai
Packt
July 2017
|
| Schlagworte: | |
| Zusammenfassung: | Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book * Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more * Analyze and extract actionable insights from your social data using various Python tools * A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What you will learn * Understand the basics of social media mining * Use PyMongo to clean, store, and access data in MongoDB * Understand user reactions and emotion detection on Facebook * Perform Twitter sentiment analysis and entity recognition using Python * Analyze video and campaign performance on YouTube * Mine popular trends on GitHub and predict the next big technology * Extract conversational topics on public internet forums * Analyze user interests on Pinterest * Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics and show you why it is important. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. You will also perform web scraping and visualize data using various tools such as plotly and matplotlib. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark |
| Beschreibung: | vi, 295 Seiten Illustrationen, Diagramme |
| ISBN: | 9781787121485 |
Internformat
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| 520 | 3 | |a Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book * Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more * Analyze and extract actionable insights from your social data using various Python tools * A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. | |
| 520 | 3 | |a What you will learn * Understand the basics of social media mining * Use PyMongo to clean, store, and access data in MongoDB * Understand user reactions and emotion detection on Facebook * Perform Twitter sentiment analysis and entity recognition using Python * Analyze video and campaign performance on YouTube * Mine popular trends on GitHub and predict the next big technology * Extract conversational topics on public internet forums * Analyze user interests on Pinterest * Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics and show you why it is important. | |
| 520 | 3 | |a Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. You will also perform web scraping and visualize data using various tools such as plotly and matplotlib. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark | |
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| institution | BVB |
| isbn | 9781787121485 |
| language | English |
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| spelling | Chatterjee, Siddhartha 1963- (DE-588)124061795X aut Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more Siddhartha Chatterjee, Michal Krystyanczuk Birmingham ; Mumbai Packt July 2017 vi, 295 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book * Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more * Analyze and extract actionable insights from your social data using various Python tools * A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What you will learn * Understand the basics of social media mining * Use PyMongo to clean, store, and access data in MongoDB * Understand user reactions and emotion detection on Facebook * Perform Twitter sentiment analysis and entity recognition using Python * Analyze video and campaign performance on YouTube * Mine popular trends on GitHub and predict the next big technology * Extract conversational topics on public internet forums * Analyze user interests on Pinterest * Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics and show you why it is important. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. You will also perform web scraping and visualize data using various tools such as plotly and matplotlib. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark Visualisierung (DE-588)4188417-6 gnd rswk-swf Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf Social Media (DE-588)4639271-3 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Datenstruktur (DE-588)4011146-5 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Datenspeicherung (DE-588)4332175-6 gnd rswk-swf Datenanalyse (DE-588)4123037-1 s Social Media (DE-588)4639271-3 s Python Programmiersprache (DE-588)4434275-5 s DE-604 Data Mining (DE-588)4428654-5 s Datenspeicherung (DE-588)4332175-6 s Datenstruktur (DE-588)4011146-5 s Visualisierung (DE-588)4188417-6 s Krystyanczuk, Michal (DE-588)1240618409 aut |
| spellingShingle | Chatterjee, Siddhartha 1963- Krystyanczuk, Michal Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more Visualisierung (DE-588)4188417-6 gnd Python Programmiersprache (DE-588)4434275-5 gnd Social Media (DE-588)4639271-3 gnd Datenanalyse (DE-588)4123037-1 gnd Datenstruktur (DE-588)4011146-5 gnd Data Mining (DE-588)4428654-5 gnd Datenspeicherung (DE-588)4332175-6 gnd |
| subject_GND | (DE-588)4188417-6 (DE-588)4434275-5 (DE-588)4639271-3 (DE-588)4123037-1 (DE-588)4011146-5 (DE-588)4428654-5 (DE-588)4332175-6 |
| title | Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more |
| title_auth | Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more |
| title_exact_search | Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more |
| title_exact_search_txtP | Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more |
| title_full | Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more Siddhartha Chatterjee, Michal Krystyanczuk |
| title_fullStr | Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more Siddhartha Chatterjee, Michal Krystyanczuk |
| title_full_unstemmed | Python social media analytics analyze and visualize data from Twitter, YouTube, GitHub, and more Siddhartha Chatterjee, Michal Krystyanczuk |
| title_short | Python social media analytics |
| title_sort | python social media analytics analyze and visualize data from twitter youtube github and more |
| title_sub | analyze and visualize data from Twitter, YouTube, GitHub, and more |
| topic | Visualisierung (DE-588)4188417-6 gnd Python Programmiersprache (DE-588)4434275-5 gnd Social Media (DE-588)4639271-3 gnd Datenanalyse (DE-588)4123037-1 gnd Datenstruktur (DE-588)4011146-5 gnd Data Mining (DE-588)4428654-5 gnd Datenspeicherung (DE-588)4332175-6 gnd |
| topic_facet | Visualisierung Python Programmiersprache Social Media Datenanalyse Datenstruktur Data Mining Datenspeicherung |
| work_keys_str_mv | AT chatterjeesiddhartha pythonsocialmediaanalyticsanalyzeandvisualizedatafromtwitteryoutubegithubandmore AT krystyanczukmichal pythonsocialmediaanalyticsanalyzeandvisualizedatafromtwitteryoutubegithubandmore |