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Social Network Data Analytics

Social Network Data Analytics Book
Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
Release : 2011-03-18
ISBN : 1441984623
Language : En, Es, Fr & De

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Book Description :

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.

Social Network Analysis

Social Network Analysis Book
Author : Stanley Wasserman,Katherine Faust,Stanley (University of Illinois Wasserman, Urbana-Champaign)
Publisher : Cambridge University Press
Release : 1994-11-25
ISBN : 9780521387071
Language : En, Es, Fr & De

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Book Description :

Covers methods for the analysis of social networks and applies them to examples.

Social Network Analytics for Contemporary Business Organizations

Social Network Analytics for Contemporary Business Organizations Book
Author : Bansal, Himani,Shrivastava, Gulshan,Nguyen, Gia Nhu,Stanciu, Loredana-Mihaela
Publisher : IGI Global
Release : 2018-03-23
ISBN : 1522550984
Language : En, Es, Fr & De

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Book Description :

Social technology is quickly becoming a vital tool in our personal, educational, and professional lives. Its use must be further examined in order to determine the role of social media technology in organizational settings to promote business development and growth. Social Network Analytics for Contemporary Business Organizations is a critical scholarly resource that analyzes the application of social media in business applications. Featuring coverage on a broad range of topics, such as business management, dynamic networks, and online interaction, this book is geared towards professionals, researchers, academics, students, managers, and practitioners actively involved in the business industry.

Mixed Methods Social Network Analysis

Mixed Methods Social Network Analysis Book
Author : Dominik E. Froehlich,Martin Rehm,Bart C. Rienties
Publisher : Routledge
Release : 2019-12-09
ISBN : 0429557043
Language : En, Es, Fr & De

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Book Description :

Mixed Methods Social Network Analysis brings together diverse perspectives from 42 international experts on how to design, implement, and evaluate mixed methods social network analysis (MMSNA). There is an increased recognition that social networks can be important catalysts for change and transformation. This edited book from leading experts in mixed methods and social network analysis describes how researchers can conceptualize, develop, mix, and intersect diverse approaches, concepts, and tools. In doing so, they can improve their understanding and insights into the complex change processes in social networks. Section 1 includes eight chapters that reflect on "Why should we do MMSNA?", providing a clear map of MMSNA research to date and why to consider MMSNA. In Section 2 the remaining 11 chapters are dedicated to the question "How do I do MMSNA?", illustrating how concentric circles, learning analytics, qualitative structured approaches, relational event modeling, and other approaches can empower researchers. This book shows that mixing qualitative and quantitative approaches to social network analysis can empower people to understand the complexities of change in networks and relations between people. It shows how mixed analysis can be applied to a wide range of data generated by diverse global communities: American school children, Belgian teachers, Dutch medical professionals, Finnish consultants, French school children, and Swedish right-wing social media users, amongst others. It will be of great interest to researchers and postgraduate students in education and social sciences and mixed methods scholars.

Big Data and Social Media Analytics

Big Data and Social Media Analytics Book
Author : Anonim
Publisher : Springer Nature
Release : 2021
ISBN : 3030670449
Language : En, Es, Fr & De

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Book Description :

This edited book provides techniques which address various aspects of big data collection and analysis from social media platforms and beyond. It covers efficient compression of large networks, link prediction in hashtag graphs, visual exploration of social media data, identifying motifs in multivariate data, social media surveillance to enhance search and rescue missions, recommenders for collaborative filtering and safe travel plans to high risk destinations, analysis of cyber influence campaigns on YouTube, impact of location on business rating, bibliographical and co-authorship network analysis, and blog data analytics. All these trending topics form a major part of the state of the art in social media and big data analytics. Thus, this edited book may be considered as a valuable source for readers interested in grasping some of the most recent advancements in this high trending domain.

Learning Social Media Analytics with R

Learning Social Media Analytics with R Book
Author : Raghav Bali,Dipanjan Sarkar,Tushar Sharma
Publisher : Packt Publishing Ltd
Release : 2017-05-26
ISBN : 1787125467
Language : En, Es, Fr & De

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Book Description :

Tap into the realm of social media and unleash the power of analytics for data-driven insights using R About This Book A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms. Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering. Who This Book Is For It is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise. What You Will Learn Learn how to tap into data from diverse social media platforms using the R ecosystem Use social media data to formulate and solve real-world problems Analyze user social networks and communities using concepts from graph theory and network analysis Learn to detect opinion and sentiment, extract themes, topics, and trends from unstructured noisy text data from diverse social media channels Understand the art of representing actionable insights with effective visualizations Analyze data from major social media channels such as Twitter, Facebook, Flickr, Foursquare, Github, StackExchange, and so on Learn to leverage popular R packages such as ggplot2, topicmodels, caret, e1071, tm, wordcloud, twittR, Rfacebook, dplyr, reshape2, and many more In Detail The Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how analytics can be leveraged to derive insights from it. This data can be analyzed to gain valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers frame business problems and solve them using social data. The book will also cover several practical real-world use cases on social media using R and its advanced packages to utilize data science methodologies such as sentiment analysis, topic modeling, text summarization, recommendation systems, social network analysis, classification, and clustering. This will enable readers to learn different hands-on approaches to obtain data from diverse social media sources such as Twitter and Facebook. It will also show readers how to establish detailed workflows to process, visualize, and analyze data to transform social data into actionable insights. Style and approach This book follows a step-by-step approach with detailed strategies for understanding, extracting, analyzing, visualizing, and modeling data from several major social network platforms such as Facebook, Twitter, Foursquare, Flickr, Github, and StackExchange. The chapters cover several real-world use cases and leverage data science, machine learning, network analysis, and graph theory concepts along with the R ecosystem, including popular packages such as ggplot2, caret,dplyr, topicmodels, tm, and so on.

Fraud Analytics Using Descriptive Predictive and Social Network Techniques

Fraud Analytics Using Descriptive  Predictive  and Social Network Techniques Book
Author : Bart Baesens,Wouter Verbeke,Veronique Van Vlasselaer
Publisher : John Wiley & Sons
Release : 2015-08-17
ISBN : 1119133122
Language : En, Es, Fr & De

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Book Description :

Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post–implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti–money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.

Analyzing Social Media Networks with NodeXL

Analyzing Social Media Networks with NodeXL Book
Author : Derek Hansen,Ben Shneiderman,Marc A. Smith,Itai Himelboim
Publisher : Morgan Kaufmann
Release : 2019-05-08
ISBN : 0128177578
Language : En, Es, Fr & De

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Book Description :

Analyzing Social Media Networks with NodeXL: Insights from a Connected World, Second Edition, provides readers with a thorough, practical and updated guide to NodeXL, the open-source social network analysis (SNA) plug-in for use with Excel. The book analyzes social media, provides a NodeXL tutorial, and presents network analysis case studies, all of which are revised to reflect the latest developments. Sections cover history and concepts, mapping and modeling, the detailed operation of NodeXL, and case studies, including e-mail, Twitter, Facebook, Flickr and YouTube. In addition, there are descriptions of each system and types of analysis for identifying people, documents, groups and events. This book is perfect for use as a course text in social network analysis or as a guide for practicing NodeXL users. Walks users through NodeXL while also explaining the theory and development behind each step Demonstrates how visual analytics research can be applied to SNA tools for the mass market Includes updated case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and Instagram Includes downloadable companion materials and online resources at https://www.smrfoundation.org/nodexl/teaching-with-nodexl/teaching-resources/

Social Network Analysis in Telecommunications

Social Network Analysis in Telecommunications Book
Author : Carlos Andre Reis Pinheiro
Publisher : John Wiley & Sons
Release : 2011-05-09
ISBN : 1118010957
Language : En, Es, Fr & De

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Book Description :

A timely look at effective use of social network analysis within the telecommunications industry to boost customer relationships The key to any successful company is the relationship that it builds with its customers. This book shows how social network analysis, analytics, and marketing knowledge can be combined to create a positive customer experience within the telecommunications industry. Reveals how telecommunications companies can effectively enhance their relationships with customers Provides the groundwork for defining social network analysis Defines the tools that can be used to address social network problems A must-read for any professionals eager to distinguish their products in the marketplace, this book shows you how to get it done right, with social network analysis.

Open Source Intelligence and Cyber Crime

Open Source Intelligence and Cyber Crime Book
Author : Mohammad A. Tayebi,Uwe Glässer,David B. Skillicorn
Publisher : Springer Nature
Release : 2020-09-01
ISBN : 3030412512
Language : En, Es, Fr & De

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Book Description :

This book shows how open source intelligence can be a powerful tool for combating crime by linking local and global patterns to help understand how criminal activities are connected. Readers will encounter the latest advances in cutting-edge data mining, machine learning and predictive analytics combined with natural language processing and social network analysis to detect, disrupt, and neutralize cyber and physical threats. Chapters contain state-of-the-art social media analytics and open source intelligence research trends. This multidisciplinary volume will appeal to students, researchers, and professionals working in the fields of open source intelligence, cyber crime and social network analytics. Chapter Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Social Network Analysis Applied to Team Sports Analysis

Social Network Analysis Applied to Team Sports Analysis Book
Author : Filipe Manuel Clemente,Fernando Manuel Lourenço Martins,Rui Sousa Mendes
Publisher : Springer
Release : 2015-11-16
ISBN : 9783319258546
Language : En, Es, Fr & De

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Book Description :

Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

Social Network Analytics

Social Network Analytics Book
Author : Nilanjan Dey,Samarjeet Borah,Rosalina Babo,Amira S. Ashour
Publisher : Academic Press
Release : 2018-11-16
ISBN : 0128156414
Language : En, Es, Fr & De

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Book Description :

Social Network Analytics: Computational Research Methods and Techniques focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, it includes a variety of applications from several domains, such as scientific research, and the business and industrial sectors. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, the big data analytics of social networks, multidimensional scaling, and more. As analyzing social network data is rapidly gaining interest in the scientific research community because of the importance of the information and insights that can be culled from the wealth of data inherent in the various aspects of the network, this book provides insights on measuring the relationships and flows between people, groups, organizations, computers, URLs, and more. Examines a variety of data analytic techniques that can be applied to social networks Discusses various methods of visualizing, modeling and tracking network patterns, organization, growth and change Covers the most recent research on social network analysis and includes applications to a number of domains

Social Media Analytics for User Behavior Modeling

Social Media Analytics for User Behavior Modeling Book
Author : ARUN REDDY. HE NELAKURTHI (JINGRUI.),Jingrui He
Publisher : CRC Press
Release : 2020-01-06
ISBN : 9780367211585
Language : En, Es, Fr & De

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Book Description :

In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.

Data Mining for Social Network Data

Data Mining for Social Network Data Book
Author : Nasrullah Memon,Jennifer Jie Xu,David L. Hicks,Hsinchun Chen
Publisher : Springer
Release : 2010-07-09
ISBN : 9781441962867
Language : En, Es, Fr & De

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Book Description :

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.

Creating Value with Social Media Analytics

Creating Value with Social Media Analytics Book
Author : Gohar F. Khan
Publisher : Createspace Independent Publishing Platform
Release : 2018-04-23
ISBN : 9781977543974
Language : En, Es, Fr & De

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Book Description :

Often termed as the ''new gold,'' the vast amount of social media data can be employed to identify which customer behavior and actions create more value. Nevertheless, many brands find it extremely hard to define what the value of social media is and how to capture and create value with social media data.In Creating Value with Social Media Analytics, we draw on developments in social media analytics theories and tools to develop a comprehensive social media value creation framework that allows readers to define, align, capture, and sustain value through social media data. The book offers concepts, strategies, tools, tutorials, and case studies that brands need to align, extract, and analyze a variety of social media data, including text, actions, networks, multimedia, apps, hyperlinks, search engines, and location data. By the end of this book, the readers will have mastered the theories, concepts, strategies, techniques, and tools necessary to extract business value from big social media that help increase brand loyalty, generate leads, drive traffic, and ultimately make sound business decisions. Here is how the book is organized. Chapter 1: Creating Value with Social Media Analytics Chapter 2: Understanding Social Media Chapter 3: Understanding Social Media Analytics Chapter 4: Analytics-Business Alignment Chapter 5: Capturing Value with Network Analytics Chapter 6: Capturing Value with Text Analytics Chapter 7: Capturing Value with Actions Analytics Chapter 8: Capturing Value with Search Engine Analytics Chapter 9: Capturing Value with Location Analytics Chapter 10: Capturing Value with Hyperlinks Analytics Chapter 11: Capturing Value with Mobile Analytics Chapter 12: Capturing Value with Multimedia Analytics Chapter 13: Social Media Analytics CapabilitiesChapter 14: Social Media Security, Privacy, & Ethics The book has a companion site (https://analytics-book.com/), which offers useful instructor resources. Praises for the book "Gohar F. Khan has a flair for simplifying the complexity of social media analytics. Creating Value with Social Media Analytics is a beautifully delineated roadmap to creating and capturing business value through social media. It provides the theories, tools, and creates a roadmap to leveraging social media data for business intelligence purposes. Real world analytics cases and tutorials combined with a comprehensive companion site make this an excellent textbook for both graduate and undergraduate students."-Robin Saunders, Director of the Communications and Information Management Graduate Programs, Bay Path University. "Creating Value with Social Media Analytics offers a comprehensive framework to define, align, capture, and sustain business value through social media data. The book is theoretically grounded and practical, making it an excellent resource for social media analytics courses."-Haya Ajjan, Director & Associate Prof., Elon Center for Organizational Analytics, Elon University. "Gohar Khan is a pioneer in the emerging domain of social media analytics. This latest text is a must-read for business leaders, managers, and academicians, as it provides a clear and concise understanding of business value creation with social media data from a social lens."-Laeeq Khan, Director, Social Media Analytics Research Team, Ohio University. "Whether you are coming from a business, research, science or art background, Creating Value with Social Media Analytics is a brilliant induction resource for those entering the social media analytics industry. The insightful case studies and carefully crafted tutorials are the perfect supplements to help digest the key concepts introduced in each chapter."-Jared Wong, Social Media Data Analyst, Digivizer "It is one of the most comprehensive books on analytics that I have come across recently."-Bobby Swar, Prof. Concordia Uni.

Social Networks Social Network Analysis in Companies

Social Networks   Social Network Analysis in Companies Book
Author : Markus Hoffmann
Publisher : GRIN Verlag
Release : 2013-09
ISBN : 3656020574
Language : En, Es, Fr & De

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Book Description :

Seminar paper from the year 2011 in the subject Business economics - Marketing, Corporate Communication, CRM, Market Research, Social Media, grade: -, Management Center Innsbruck, language: English, abstract: This term paper is about Social Networks, Social Network Analysis, as well as its use in marketing and its history. Chapter 2 "The Internal Power of Social Networks" is about the question of what a Social Network is and about the History of Social Network Analysis. It also examines social networks in companies, the question of how executives can create energy in companies and the most common problems that typically come along with social networks in companies. Chapter 3 "The External Use of Social Networks" explains how companies can gain and maintain social capital and make use of the modern forms of social media. It also gives some general advise on the most popular social networking platforms.

Social Network Analysis 109 Success Secrets 109 Most Asked Questions on Social Network Analysis What You Need to Know

Social Network Analysis 109 Success Secrets   109 Most Asked Questions on Social Network Analysis   What You Need to Know Book
Author : Irene Weeks
Publisher : Emereo Publishing
Release : 2014-02
ISBN : 9781488527616
Language : En, Es, Fr & De

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Book Description :

Social net-work analysis' ('SNA') is the examination of communal networks. Social net-work examination perspectives communal connections in specifications of net-work hypothesis, containing of nodes (representing single performers inside the network) and links (which constitute connections amid the single human beings, such like amity, affinity, corporations, intimate networksexual connections, etcetera.) These networks are frequently portrayed in a communal net-work figure, where knots are constituted like details and links are constituted like rules. There has never been a Social Network Analysis Guide like this. It contains 109 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about Social Network Analysis. A quick look inside of some of the subjects covered: Social network - Indigenous theories, Social network - Organizations, Graph drawing - Software, Social networks - Meso level, Computer and network surveillance - Social network analysis, KXEN Inc. - Predictive Analytics, Social software - Debates or design choices, Social networks - Indigenous theories, Natural resource management - Stakeholder analysis, Use of Twitter by public figures - Reference bibliography, Knowledge management Research, Social network - Meso level, Barry Wellman - Social network theory, Social network - Levels of analysis, Social network - Textbooks and educational resources, Barry Wellman - Offices, Social networking service - Data mining, Computer-supported collaboration - Telework and human capital management, Social network analysis - Practical applications, Social network change detection, Social science - Sociology, Douglas R. White - Books and much more...

Social Media Analytics Strategy

Social Media Analytics Strategy Book
Author : Alex Gonçalves
Publisher : Apress
Release : 2017-11-15
ISBN : 9781484231012
Language : En, Es, Fr & De

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Book Description :

This book shows you how to use social media analytics to optimize your business performance. The tools discussed will prepare you to create and implement an effective digital marketing strategy. From understanding the data and its sources to detailed metrics, dashboards, and reports, this book is a robust tool for anyone seeking a tangible return on investment from social media and digital marketing. Social Media Analytics Strategy speaks to marketers who do not have a technical background and creates a bridge into the digital world. Comparable books are either too technical for marketers (aimed at software developers) or too basic and do not take strategy into account. They also lack an overview of the entire process around using analytics within a company project. They don’t go into the everyday details and also don’t touch upon common mistakes made by marketers. This book highlights patterns of common challenges experienced by marketers from entry level to directors and C-level executives. Social media analytics are explored and explained using real-world examples and interviews with experienced professionals and founders of social media analytics companies. What You’ll Learn Get a clear view of the available data for social media marketing and how to access all of it Make use of data and information behind social media networks to your favor Know the details of social media analytics tools and platforms so you can use any tool in the market Apply social media analytics to many different real-world use cases Obtain tips from interviews with professional marketers and founders of social media analytics platforms Understand where social media is heading, and what to expect in the future Who This Book Is For Marketing professionals, social media marketing specialists, analysts up to directors and C-level executives, marketing students, and teachers of social media analytics/social media marketing

Python Social Media Analytics

Python Social Media Analytics Book
Author : Siddhartha Chatterjee,Michal Krystyanczuk
Publisher : Unknown
Release : 2017-04-28
ISBN : 9781787121485
Language : En, Es, Fr & De

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Book Description :

Leverage the power of Python to collect, process, and mine deep insights from social media dataAbout 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 scaleWho This Book Is ForIf 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 cloudIn DetailSocial 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.

Learning Social Media Analytics with R

Learning Social Media Analytics with R Book
Author : Raghav Bali,Dipanjan Sarkar,Tushar Sharma
Publisher : Unknown
Release : 2017-05-26
ISBN : 9781787127524
Language : En, Es, Fr & De

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Book Description :

Tap into the realm of social media and unleash the power of analytics for data-driven insights using RAbout This Book* A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data* Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms.* Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering.Who This Book Is ForIt is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise.What You Will Learn* Learn how to tap into data from diverse social media platforms using the R ecosystem* Use social media data to formulate and solve real-world problems* Analyze user social networks and communities using concepts from graph theory and network analysis* Learn to detect opinion and sentiment, extract themes, topics, and trends from unstructured noisy text data from diverse social media channels* Understand the art of representing actionable insights with effective visualizations* Analyze data from major social media channels such as Twitter, Facebook, Flickr, Foursquare, Github, StackExchange, and so on* Learn to leverage popular R packages such as ggplot2, topicmodels, caret, e1071, tm, wordcloud, twittR, Rfacebook, dplyr, reshape2, and many moreIn DetailThe Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how analytics can be leveraged to derive insights from it. This data can be analyzed to gain valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers frame business problems and solve them using social data.The book will also cover several practical real-world use cases on social media using R and its advanced packages to utilize data science methodologies such as sentiment analysis, topic modeling, text summarization, recommendation systems, social network analysis, classification, and clustering. This will enable readers to learn different hands-on approaches to obtain data from diverse social media sources such as Twitter and Facebook. It will also show readers how to establish detailed workflows to process, visualize, and analyze data to transform social data into actionable insights.Style and approachThis book follows a step-by-step approach with detailed strategies for understanding, extracting, analyzing, visualizing, and modeling data from several major social network platforms such as Facebook, Twitter, Foursquare, Flickr, Github, and StackExchange. The chapters cover several real-world use cases and leverage data science, machine learning, network analysis, and graph theory concepts along with the R ecosystem, including popular packages such as ggplot2, caret,dplyr, topicmodels, tm, and so on.