Mining Social Media

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Mining Social Media

Author : Lam Thuy Vo
Publisher : No Starch Press
ISBN 13 : 1593279175
Total Pages : 210 pages
Book Rating : 4.5/5 (932 download)

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Book Synopsis Mining Social Media by : Lam Thuy Vo

Download or read book Mining Social Media written by Lam Thuy Vo and published by No Starch Press. This book was released on 2019-12-10 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: BuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language. Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: Write Python scripts and use APIs to gather data from the social web Download data archives and dig through them for insights Inspect HTML downloaded from websites for useful content Format, aggregate, sort, and filter your collected data using Google Sheets Create data visualizations to illustrate your discoveries Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library Apply what you've learned to research topics on your own Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.

Social Media Mining

Author : Reza Zafarani
Publisher : Cambridge University Press
ISBN 13 : 1107018854
Total Pages : 337 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Social Media Mining by : Reza Zafarani

Download or read book Social Media Mining written by Reza Zafarani and published by Cambridge University Press. This book was released on 2014-04-28 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrates social media, social network analysis, and data mining to provide an understanding of the potentials of social media mining.

Mining the Social Web

Author : Matthew Russell
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449388345
Total Pages : 356 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Mining the Social Web by : Matthew Russell

Download or read book Mining the Social Web written by Matthew Russell and published by "O'Reilly Media, Inc.". This book was released on 2011-01-21 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides information on data analysis from a vareity of social networking sites, including Facebook, Twitter, and LinkedIn.

Mastering Social Media Mining with Python

Author : Marco Bonzanini
Publisher : Packt Publishing Ltd
ISBN 13 : 1783552026
Total Pages : 333 pages
Book Rating : 4.7/5 (835 download)

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Book Synopsis Mastering Social Media Mining with Python by : Marco Bonzanini

Download or read book Mastering Social Media Mining with Python written by Marco Bonzanini and published by Packt Publishing Ltd. This book was released on 2016-07-29 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acquire and analyze data from all corners of the social web with Python About This Book Make sense of highly unstructured social media data with the help of the insightful use cases provided in this guide Use this easy-to-follow, step-by-step guide to apply analytics to complicated and messy social data This is your one-stop solution to fetching, storing, analyzing, and visualizing social media data Who This Book Is For This book is for intermediate Python developers who want to engage with the use of public APIs to collect data from social media platforms and perform statistical analysis in order to produce useful insights from data. The book assumes a basic understanding of the Python Standard Library and provides practical examples to guide you toward the creation of your data analysis project based on social data. What You Will Learn Interact with a social media platform via their public API with Python Store social data in a convenient format for data analysis Slice and dice social data using Python tools for data science Apply text analytics techniques to understand what people are talking about on social media Apply advanced statistical and analytical techniques to produce useful insights from data Build beautiful visualizations with web technologies to explore data and present data products In Detail Your social media is filled with a wealth of hidden data – unlock it with the power of Python. Transform your understanding of your clients and customers when you use Python to solve the problems of understanding consumer behavior and turning raw data into actionable customer insights. This book will help you acquire and analyze data from leading social media sites. It will show you how to employ scientific Python tools to mine popular social websites such as Facebook, Twitter, Quora, and more. Explore the Python libraries used for social media mining, and get the tips, tricks, and insider insight you need to make the most of them. Discover how to develop data mining tools that use a social media API, and how to create your own data analysis projects using Python for clear insight from your social data. Style and approach This practical, hands-on guide will help you learn everything you need to perform data mining for social media. Throughout the book, we take an example-oriented approach to use Python for data analysis and provide useful tips and tricks that you can use in day-to-day tasks.

Mining the Social Web

Author : Matthew A. Russell
Publisher : O'Reilly Media
ISBN 13 : 1491973528
Total Pages : 425 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Mining the Social Web by : Matthew A. Russell

Download or read book Mining the Social Web written by Matthew A. Russell and published by O'Reilly Media. This book was released on 2018-12-04 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re located—using Python code examples, Jupyter notebooks, or Docker containers. In part one, each standalone chapter focuses on one aspect of the social landscape, including each of the major social sites, as well as web pages, blogs and feeds, mailboxes, GitHub, and a newly added chapter covering Instagram. Part two provides a cookbook with two dozen bite-size recipes for solving particular issues with Twitter. Get a straightforward synopsis of the social web landscape Use Docker to easily run each chapter’s example code, packaged as a Jupyter notebook Adapt and contribute to the code’s open source GitHub repository Learn how to employ best-in-class Python 3 tools to slice and dice the data you collect Apply advanced mining techniques such as TFIDF, cosine similarity, collocation analysis, clique detection, and image recognition Build beautiful data visualizations with Python and JavaScript toolkits

Mastering Social Media Mining with R

Author : Sharan Kumar Ravindran
Publisher : Packt Publishing Ltd
ISBN 13 : 1784399671
Total Pages : 248 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis Mastering Social Media Mining with R by : Sharan Kumar Ravindran

Download or read book Mastering Social Media Mining with R written by Sharan Kumar Ravindran and published by Packt Publishing Ltd. This book was released on 2015-09-23 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extract valuable data from your social media sites and make better business decisions using R About This Book Explore the social media APIs in R to capture data and tame it Employ the machine learning capabilities of R to gain optimal business value A hands-on guide with real-world examples to help you take advantage of the vast opportunities that come with social media data Who This Book Is For If you have basic knowledge of R in terms of its libraries and are aware of different machine learning techniques, this book is for you. Those with experience in data analysis who are interested in mining social media data will find this book useful. What You Will Learn Access APIs of popular social media sites and extract data Perform sentiment analysis and identify trending topics Measure CTR performance for social media campaigns Implement exploratory data analysis and correlation analysis Build a logistic regression model to detect spam messages Construct clusters of pictures using the K-means algorithm and identify popular personalities and destinations Develop recommendation systems using Collaborative Filtering and the Apriori algorithm In Detail With an increase in the number of users on the web, the content generated has increased substantially, bringing in the need to gain insights into the untapped gold mine that is social media data. For computational statistics, R has an advantage over other languages in providing readily-available data extraction and transformation packages, making it easier to carry out your ETL tasks. Along with this, its data visualization packages help users get a better understanding of the underlying data distributions while its range of "standard" statistical packages simplify analysis of the data. This book will teach you how powerful business cases are solved by applying machine learning techniques on social media data. You will learn about important and recent developments in the field of social media, along with a few advanced topics such as Open Authorization (OAuth). Through practical examples, you will access data from R using APIs of various social media sites such as Twitter, Facebook, Instagram, GitHub, Foursquare, LinkedIn, Blogger, and other networks. We will provide you with detailed explanations on the implementation of various use cases using R programming. With this handy guide, you will be ready to embark on your journey as an independent social media analyst. Style and approach This easy-to-follow guide is packed with hands-on, step-by-step examples that will enable you to convert your real-world social media data into useful, practical information.

Social Media Data Mining and Analytics

Author : Gabor Szabo
Publisher : John Wiley & Sons
ISBN 13 : 1118824857
Total Pages : 352 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Social Media Data Mining and Analytics by : Gabor Szabo

Download or read book Social Media Data Mining and Analytics written by Gabor Szabo and published by John Wiley & Sons. This book was released on 2018-10-23 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.

Social Media Mining and Social Network Analysis: Emerging Research

Author : Xu, Guandong
Publisher : IGI Global
ISBN 13 : 1466628073
Total Pages : 347 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Social Media Mining and Social Network Analysis: Emerging Research by : Xu, Guandong

Download or read book Social Media Mining and Social Network Analysis: Emerging Research written by Xu, Guandong and published by IGI Global. This book was released on 2013-01-31 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social Media Mining and Social Network Analysis: Emerging Research highlights the advancements made in social network analysis and social web mining and its influence in the fields of computer science, information systems, sociology, organization science discipline and much more. This collection of perspectives on developmental practice is useful for industrial practitioners as well as researchers and scholars.

Community detection and mining in social media

Author : Lei Tang
Publisher : Springer Nature
ISBN 13 : 3031019008
Total Pages : 126 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Community detection and mining in social media by : Lei Tang

Download or read book Community detection and mining in social media written by Lei Tang and published by Springer Nature. This book was released on 2022-06-01 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale. This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular, we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of \emph{community detection and mining in social media}. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, some toy data sets used in the book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information. Table of Contents: Social Media and Social Computing / Nodes, Ties, and Influence / Community Detection and Evaluation / Communities in Heterogeneous Networks / Social Media Mining

Post, Mine, Repeat

Author : Helen Kennedy
Publisher : Springer
ISBN 13 : 1137353988
Total Pages : 262 pages
Book Rating : 4.1/5 (373 download)

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Book Synopsis Post, Mine, Repeat by : Helen Kennedy

Download or read book Post, Mine, Repeat written by Helen Kennedy and published by Springer. This book was released on 2016-05-14 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, Helen Kennedy argues that as social media data mining becomes more and more ordinary, as we post, mine and repeat, new data relations emerge. These new data relations are characterised by a widespread desire for numbers and the troubling consequences of this desire, and also by the possibility of doing good with data and resisting data power, by new and old concerns, and by instability and contradiction. Drawing on action research with public sector organisations, interviews with commercial social insights companies and their clients, focus groups with social media users and other research, Kennedy provides a fascinating and detailed account of living with social media data mining inside the organisations that make up the fabric of everyday life.

Social Network Data Analytics

Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
ISBN 13 : 1441984623
Total Pages : 502 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Social Network Data Analytics by : Charu C. Aggarwal

Download or read book Social Network Data Analytics written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2011-03-18 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.

Provenance Data in Social Media

Author : Geoffrey Barbier
Publisher : Springer Nature
ISBN 13 : 3031019040
Total Pages : 72 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Provenance Data in Social Media by : Geoffrey Barbier

Download or read book Provenance Data in Social Media written by Geoffrey Barbier and published by Springer Nature. This book was released on 2022-05-31 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social media shatters the barrier to communicate anytime anywhere for people of all walks of life. The publicly available, virtually free information in social media poses a new challenge to consumers who have to discern whether a piece of information published in social media is reliable. For example, it can be difficult to understand the motivations behind a statement passed from one user to another, without knowing the person who originated the message. Additionally, false information can be propagated through social media, resulting in embarrassment or irreversible damages. Provenance data associated with a social media statement can help dispel rumors, clarify opinions, and confirm facts. However, provenance data about social media statements is not readily available to users today. Currently, providing this data to users requires changing the social media infrastructure or offering subscription services. Taking advantage of social media features, research in this nascent field spearheads the search for a way to provide provenance data to social media users, thus leveraging social media itself by mining it for the provenance data. Searching for provenance data reveals an interesting problem space requiring the development and application of new metrics in order to provide meaningful provenance data to social media users. This lecture reviews the current research on information provenance, explores exciting research opportunities to address pressing needs, and shows how data mining can enable a social media user to make informed judgements about statements published in social media. Table of Contents: Information Provenance in Social Media / Provenance Attributes / Provenance via Network Information / Provenance Data

Information Retrieval and Social Media Mining

Author : María N. Moreno García
Publisher : MDPI
ISBN 13 : 3036502467
Total Pages : 144 pages
Book Rating : 4.0/5 (365 download)

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Book Synopsis Information Retrieval and Social Media Mining by : María N. Moreno García

Download or read book Information Retrieval and Social Media Mining written by María N. Moreno García and published by MDPI. This book was released on 2021-03-09 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents diverse contributions related to some of the latest advances in the field of personalization and recommender systems, as well as social media and sentiment analysis. The work comprises several articles that address different problems in these areas by means of recent techniques such as deep learning, methods to analyze the structure and the dynamics of social networks, and modern language processing approaches for sentiment analysis, among others. The proposals included in the book are representative of some highly topical research directions and cover different application domains where they have been validated. These go from the recommendation of hotels, movies, music, documents, or pharmacy cross-selling to sentiment analysis in the field of telemedicine and opinion mining on news, also including the study of social capital on social media and dynamics aspects of the Twitter social network.

Web Mining and Social Networking

Author : Guandong Xu
Publisher : Springer Science & Business Media
ISBN 13 : 144197735X
Total Pages : 210 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Web Mining and Social Networking by : Guandong Xu

Download or read book Web Mining and Social Networking written by Guandong Xu and published by Springer Science & Business Media. This book was released on 2010-10-20 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.

Mining User Generated Content

Author : Marie-Francine Moens
Publisher : CRC Press
ISBN 13 : 1466557400
Total Pages : 476 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Mining User Generated Content by : Marie-Francine Moens

Download or read book Mining User Generated Content written by Marie-Francine Moens and published by CRC Press. This book was released on 2014-01-28 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other networking sites, the social media shared by users and the associated metadata are collectively known as user generated content (UGC). To analyze UGC and glean insight about user behavior, robust techniques are needed to tackle the huge amount of real-time, multimedia, and multilingual data. Researchers must also know how to assess the social aspects of UGC, such as user relations and influential users. Mining User Generated Content is the first focused effort to compile state-of-the-art research and address future directions of UGC. It explains how to collect, index, and analyze UGC to uncover social trends and user habits. Divided into four parts, the book focuses on the mining and applications of UGC. The first part presents an introduction to this new and exciting topic. Covering the mining of UGC of different medium types, the second part discusses the social annotation of UGC, social network graph construction and community mining, mining of UGC to assist in music retrieval, and the popular but difficult topic of UGC sentiment analysis. The third part describes the mining and searching of various types of UGC, including knowledge extraction, search techniques for UGC content, and a specific study on the analysis and annotation of Japanese blogs. The fourth part on applications explores the use of UGC to support question-answering, information summarization, and recommendations.

Data Mining for Social Network Data

Author : Nasrullah Memon
Publisher : Springer
ISBN 13 : 9781441962881
Total Pages : 216 pages
Book Rating : 4.9/5 (628 download)

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Book Synopsis Data Mining for Social Network Data by : Nasrullah Memon

Download or read book Data Mining for Social Network Data written by Nasrullah Memon and published by Springer. This book was released on 2010-07-14 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, activities in open for a and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution pattern discovery using machine learning approaches and multi-agent based simulations. Editors are three rising stars in world of data mining, knowledge discovery, social network analysis, and information infrastructures, and are anchored by Springer author/editor Hsinchun Chen (Terrorism Informatics; Medical Informatics; Digital Government), who is one of the most prominent intelligence analysis and data mining experts in the world.

Web Data Mining and the Development of Knowledge-Based Decision Support Systems

Author : Sreedhar, G.
Publisher : IGI Global
ISBN 13 : 1522518789
Total Pages : 409 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Web Data Mining and the Development of Knowledge-Based Decision Support Systems by : Sreedhar, G.

Download or read book Web Data Mining and the Development of Knowledge-Based Decision Support Systems written by Sreedhar, G. and published by IGI Global. This book was released on 2016-12-21 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Websites are a central part of today’s business world; however, with the vast amount of information that constantly changes and the frequency of required updates, this can come at a high cost to modern businesses. Web Data Mining and the Development of Knowledge-Based Decision Support Systems is a key reference source on decision support systems in view of end user accessibility and identifies methods for extraction and analysis of useful information from web documents. Featuring extensive coverage across a range of relevant perspectives and topics, such as semantic web, machine learning, and expert systems, this book is ideally designed for web developers, internet users, online application developers, researchers, and faculty.