Twitter Data Analytics
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Twitter Data Analytics
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Author : Shamanth Kumar
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Twitter Data Analytics written by Shamanth Kumar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Computers categories.
This brief provides methods for harnessing Twitter data to discover solutions to complex inquiries. The brief introduces the process of collecting data through Twitter’s APIs and offers strategies for curating large datasets. The text gives examples of Twitter data with real-world examples, the present challenges and complexities of building visual analytic tools, and the best strategies to address these issues. Examples demonstrate how powerful measures can be computed using various Twitter data sources. Due to its openness in sharing data, Twitter is a prime example of social media in which researchers can verify their hypotheses, and practitioners can mine interesting patterns and build their own applications. This brief is designed to provide researchers, practitioners, project managers, as well as graduate students with an entry point to jump start their Twitter endeavors. It also serves as a convenient reference for readers seasoned in Twitter data analysis.
Twitter Data Analytics
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Author : Axel Bruns
language : en
Publisher:
Release Date : 2014
Twitter Data Analytics written by Axel Bruns and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Data mining categories.
Twitter As Data
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Author : Zachary C. Steinert-Threlkeld
language : en
Publisher:
Release Date : 2017-12-28
Twitter As Data written by Zachary C. Steinert-Threlkeld and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-28 with Computers categories.
The rise of the internet and mobile telecommunications has created the possibility of using large datasets to understand behavior at unprecedented levels of temporal and geographic resolution. Online social networks attract the most users, though users of these new technologies provide their data through multiple sources, e.g. call detail records, blog posts, web forums, and content aggregation sites. These data allow scholars to adjudicate between competing theories as well as develop new ones, much as the microscope facilitated the development of the germ theory of disease. Of those networks, Twitter presents an ideal combination of size, international reach, and data accessibility that make it the preferred platform in academic studies. Acquiring, cleaning, and analyzing these data, however, require new tools and processes. This Element introduces these methods to social scientists and provides scripts and examples for downloading, processing, and analyzing Twitter data.
Mining The Social Web
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Author : Matthew A. Russell
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2011-01-14
Mining The Social Web written by Matthew A. Russell and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-14 with Computers categories.
Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, and Google+? This refreshed edition helps you discover who’s making connections with social media, what they’re talking about, and where they’re located. You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed. Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools. Get a straightforward synopsis of the social web landscape Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+ Learn how to employ easy-to-use Python tools to slice and dice the data you collect Explore social connections in microformats with the XHTML Friends Network Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits "A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google
Python Social Media Analytics
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Author : Siddhartha Chatterjee
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-07-28
Python Social Media Analytics written by Siddhartha Chatterjee and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Computers categories.
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 how you can leverage its capabilities to empower your business. 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. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.
Proceedings Of Data Analytics And Management
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Author : Abhishek Swaroop
language : en
Publisher: Springer Nature
Release Date : 2024-01-13
Proceedings Of Data Analytics And Management written by Abhishek Swaroop and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-13 with Technology & Engineering categories.
This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.
Data Management And Analysis
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Author : Reda Alhajj
language : en
Publisher: Springer Nature
Release Date : 2019-12-20
Data Management And Analysis written by Reda Alhajj and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-20 with Computers categories.
Data management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry. Numerous types of applications and services have been studied and re-examined in this field resulting in this edited volume which includes chapters on effective approaches for dealing with the inherent complexity within data management and analysis. This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas.
Big Data Analytics
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Author : P. Krishna Reddy
language : en
Publisher: Springer
Release Date : 2017-12-04
Big Data Analytics written by P. Krishna Reddy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-04 with Computers categories.
This book constitutes the refereed conference proceedings of the 5th International Conference on Big Data Analytics, BDA 2017, held in Hyderabad, India, in December 2017. The 21 revised full papers were carefully reviewed and selected from 80 submissions and cover topics on big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis.
Tweelyzer An Approach To Sentiment Analysis Of Tweets
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Author : Durgesh Samariya
language : en
Publisher: Anchor Academic Publishing
Release Date : 2016-10-06
Tweelyzer An Approach To Sentiment Analysis Of Tweets written by Durgesh Samariya and has been published by Anchor Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-06 with Computers categories.
The ongoing trend of people using microblogging to express their thoughts on various topics has increased the need for developing computerised techniques for automatic sentiment analysis on texts that do not exceed 200 characters. Twitter is a "micro-blogging" social networking site that has a large and rapidly growing base of users. Twitter's tweets or messages are limited to 140 characters. Because of this limitation, it is more difficult to express sentiment and the classification of the tweets is difficult as well. Sentiment analysis can be done on two types: emotion and opinion. This research completely focuses on sentiment analysis of opinions. These opinions can be divided in three different classes: positive, negative and neutral ( somewhere between positive and negative). The main goal of this study is to build a model that predicts election movement and provide sentiment score from Twitter messages (which can not exceed 140 characters). In this project, the author applies a novel approach that classifies sentiment and emotions of Twitter tweets automatically in positive, negative or neutral classes. For the sentiment, first of all, tweets from twitter were retrieved and converted into the dataset. After pre-processing the data the proposed algorithm named TWEELYZER was applied to the dataset. At the end, the performance of TWEELYZER was measured in terms of accuracy and recall. In this project, all tweets of people regarding to movies, brands, actors and actresses were collected from twitter and then cleaned and analysed according to the proposed algorithm. These tweets were collected using R Studio software. Several processes took place in pre-processing the tweets. After pre-processing the data, using R Studio led to several insights.
Big Data Analysis And Deep Learning Applications
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Author : Thi Thi Zin
language : en
Publisher: Springer
Release Date : 2018-06-06
Big Data Analysis And Deep Learning Applications written by Thi Thi Zin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-06 with Technology & Engineering categories.
This book presents a compilation of selected papers from the first International Conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and regulators of aviation authorities.