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Analyzing The Social Web

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Analyzing the Social Web

Analyzing the Social Web Book
Author : Jennifer Golbeck
Publisher : Newnes
Release : 2013-02-17
ISBN : 0124058566
Language : En, Es, Fr & De

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Book Description :

Analyzing the Social Web provides a framework for the analysis of public data currently available and being generated by social networks and social media, like Facebook, Twitter, and Foursquare. Access and analysis of this public data about people and their connections to one another allows for new applications of traditional social network analysis techniques that let us identify things like who are the most important or influential people in a network, how things will spread through the network, and the nature of peoples' relationships. Analyzing the Social Web introduces you to these techniques, shows you their application to many different types of social media, and discusses how social media can be used as a tool for interacting with the online public. Presents interactive social applications on the web, and the types of analysis that are currently conducted in the study of social media. Covers the basics of network structures for beginners, including measuring methods for describing nodes, edges, and parts of the network. Discusses the major categories of social media applications or phenomena and shows how the techniques presented can be applied to analyze and understand the underlying data. Provides an introduction to information visualization, particularly network visualization techniques, and methods for using them to identify interesting features in a network, generate hypotheses for analysis, and recognize patterns of behavior. Includes a supporting website with lecture slides, exercises, and downloadable social network data sets that can be used can be used to apply the techniques presented in the book.

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/

Analyzing Social Media Networks with NodeXL

Analyzing Social Media Networks with NodeXL Book
Author : Derek Hansen,Ben Shneiderman,Marc A. Smith
Publisher : Morgan Kaufmann
Release : 2010-09-14
ISBN : 9780123822307
Language : En, Es, Fr & De

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Book Description :

Analyzing Social Media Networks with NodeXL offers backgrounds in information studies, computer science, and sociology. This book is divided into three parts: analyzing social media, NodeXL tutorial, and social-media network analysis case studies. Part I provides background in the history and concepts of social media and social networks. Also included here is social network analysis, which flows from measuring, to mapping, and modeling collections of connections. The next part focuses on the detailed operation of the free and open-source NodeXL extension of Microsoft Excel, which is used in all exercises throughout this book. In the final part, each chapter presents one form of social media, such as e-mail, Twitter, Facebook, Flickr, and Youtube. In addition, there are descriptions of each system, the nature of networks when people interact, and types of analysis for identifying people, documents, groups, and events. Walks you through NodeXL, while explaining the theory and development behind each step, providing takeaways that can apply to any SNA Demonstrates how visual analytics research can be applied to SNA tools for the mass market Includes case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and wikis Download companion materials and resources at https://nodexl.codeplex.com/documentation

Mining and Analyzing Social Networks

Mining and Analyzing Social Networks Book
Author : I-Hsien Ting,Hui-Ju Wu,Tien-Hwa Ho
Publisher : Springer Science & Business Media
Release : 2010-05-29
ISBN : 3642134211
Language : En, Es, Fr & De

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Book Description :

Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means.

Analyzing and Securing Social Networks

Analyzing and Securing Social Networks Book
Author : Bhavani Thuraisingham,Satyen Abrol,Raymond Heatherly,Murat Kantarcioglu,Vaibhav Khadilkar,Latifur Khan
Publisher : CRC Press
Release : 2016-04-06
ISBN : 1482243288
Language : En, Es, Fr & De

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Book Description :

Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technologies that ensure the privacy of the participants of the network as well as provide controlled access to the information posted and exchanged by the participants. The authors explore security and privacy issues for social media systems, analyze such systems, and discuss prototypes they have developed for social media systems whose data are represented using semantic web technologies. These experimental systems have been developed at The University of Texas at Dallas. The material in this book, together with the numerous references listed in each chapter, have been used for a graduate-level course at The University of Texas at Dallas on analyzing and securing social media. Several experimental systems developed by graduate students are also provided. The book is divided into nine main sections: (1) supporting technologies, (2) basics of analyzing and securing social networks, (3) the authors’ design and implementation of various social network analytics tools, (4) privacy aspects of social networks, (5) access control and inference control for social networks, (6) experimental systems designed or developed by the authors on analyzing and securing social networks, (7) social media application systems developed by the authors, (8) secure social media systems developed by the authors, and (9) some of the authors’ exploratory work and further directions.

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.

Methods for Analyzing Social Media

Methods for Analyzing Social Media Book
Author : Klaus Bredl
Publisher : Routledge
Release : 2017-07-05
ISBN : 1351558404
Language : En, Es, Fr & De

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Book Description :

Social media is becoming increasingly attractive for users. It is a fast way to communicate ideas and a key source of information. It is therefore one of the most influential mediums of communication of our time and an important area for audience research. The growth of social media invites many new questions such as: How can we analyze social media? Can we use traditional audience research methods and apply them to online content? Which new research strategies have been developed? Which ethical research issues and controversies do we have to pay attention to? This book focuses on research strategies and methods for analyzing social media and will be of interest to researchers and practitioners using social media, as well as those wanting to keep up to date with the subject. This book was originally published as a special issue of the Journal of Technology in Human Services.

On the Move to Meaningful Internet Systems OTM 2008

On the Move to Meaningful Internet Systems  OTM 2008 Book
Author : Zahir Tari
Publisher : Springer Science & Business Media
Release : 2008-10-23
ISBN : 3540888721
Language : En, Es, Fr & De

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Book Description :

the second covering the issues of security in complex Internet-based information systems. Eachof these ?ve conferencesencouragesresearchersto treattheir respective topics within a framework that incorporates jointly (a) theory, (b) conceptual design and development, and (c) applications, in particular case studies and industrial solutions. Following and expanding the model created in 2003, we again solicited and selected quality workshop proposals to complement the more “archival” nature of the main conferences with research results in a number of selected and more “avant-garde”areasrelatedtothegeneraltopicofdistributedcomputing. For- stance, the so-called Semantic Web has given rise to severalnovel research areas combining linguistics, informationsystems technology,andarti?cialintelligence, such as the modeling of (legal) regulatory systems and the ubiquitous nature of theirusage. WeweregladtoseethatinspiteofOnTheMoveswitchingsidesofthe Atlantic, seven of our earlier successful workshops (notably AweSOMe, SWWS, ORM,OnToContent,MONET,PerSys,RDDS) re-appearedin2008withathird or even fourth edition, sometimes by alliance with other newly emerging wo- shops, and that no fewer than seven brand-newindependent workshopscould be selected from proposals and hosted: ADI, COMBEK, DiSCo, IWSSA, QSI and SEMELS. Workshop audiences productively mingled with each other and with those of the main conferences, and there was considerable overlap in authors. The OTM organizers are especially grateful for the leadership, diplomacy and competence of Dr. Pilar Herrero in managing this complex and delicate process for the ?fth consecutive year.

Mining the Social Web

Mining the Social Web Book
Author : Matthew A. Russell,Matthew Russell
Publisher : "O'Reilly Media, Inc."
Release : 2011-01-21
ISBN : 1449388345
Language : En, Es, Fr & De

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Book Description :

Provides information on data analysis from a vareity of social networking sites, including Facebook, Twitter, and LinkedIn.

NetNet a Tool for Simplifying the Workflow of Analyzing Social Networks with Textual Content

NetNet  a Tool for Simplifying the Workflow of Analyzing Social Networks with Textual Content Book
Author : Jun Hao
Publisher : Unknown
Release : 2020
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Today’s online social networks produce a significant amount of data that contain rich information. A key challenge is to analyze and make sense of the data. In many application scenarios, this requires analyzing both network topology information and textual content contained in the network. However, existing network analysis tools usually focus on one of these aspects, instead of providing end-to-end solutions for this particular research scenario. Therefore, users often need to utilize several different frameworks/tools with a complex workflow. In this thesis, we present NetNet, a social network analysis tool that is specifically designed to simplify the workflow of analyzing social networks containing both complicated network structure and massive textual information. In NetNet, we model social networks as interconnected user nodes with text nodes associated with them and leverage network analysis and text mining algorithms to seamlessly perform both tasks. In addition, our design utilizes web technologies to bundle the complicated workflow of data importing, network analysis, text analysis, and result delivery with a simple and efficient user interface. We evaluate the performance of our design with multiple sets of experiments on five datasets. The result shows that our design is practically efficient and scalable. We also perform a case study with NetNet to demonstrate how the workflow of analyzing social networks with textual contents is simplified.

Analyzing Social Networks

Analyzing Social Networks Book
Author : Stephen P Borgatti,Martin G Everett,Jeffrey C Johnson
Publisher : SAGE
Release : 2018-01-08
ISBN : 1526418487
Language : En, Es, Fr & De

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Book Description :

Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis. Using simple language and equations, the authors provide expert, clear insight into every step of the research process -- including basic maths principles -- without making assumptions about what you know. With a particular focus on NetDraw and UCINET, the book introduces relevant software tools step-by-step in an easy to follow way. In addition to the fundamentals of network analysis and the research process, this new edition focuses on: Digital data and social networks like Twitter Statistical models to use in SNA, like QAP and ERGM The structure and centrality of networks Methods for cohesive subgroups/community detection Supported by new chapter exercises, a glossary, and a fully updated companion website, this edition is the perfect student-friendly introduction to social network analysis.

Graph Theoretic Approaches for Analyzing Large Scale Social Networks

Graph Theoretic Approaches for Analyzing Large Scale Social Networks Book
Author : Meghanathan, Natarajan
Publisher : IGI Global
Release : 2017-07-13
ISBN : 1522528156
Language : En, Es, Fr & De

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Book Description :

Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information. Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.

Analyzing Social Media Data and Web Networks

Analyzing Social Media Data and Web Networks Book
Author : M. Cantijoch,R. Gibson,S. Ward
Publisher : Springer
Release : 2014-11-25
ISBN : 1137276770
Language : En, Es, Fr & De

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Book Description :

As governments, citizens and organizations have moved online there is an increasing need for academic enquiry to adapt to this new context for communication and political action. This adaptation is crucially dependent on researchers being equipped with the necessary methodological tools to extract, analyze and visualize patterns of web activity. This volume profiles the latest techniques being employed by social scientists to collect and interpret data from some of the most popular social media applications, the political parties' own online activist spaces, and the wider system of hyperlinks that structure the inter-connections between these sites. Including contributions from a range of academic disciplines including Political Science, Media and Communication Studies, Economics, and Computer Science, this study showcases a new methodological approach that has been expressly designed to capture and analyze web data in the process of investigating substantive questions.

Web Mining and Social Networking

Web Mining and Social Networking Book
Author : Guandong Xu,Yanchun Zhang,Lin Li
Publisher : Springer Science & Business Media
Release : 2010-10-20
ISBN : 9781441977359
Language : En, Es, Fr & De

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Book Description :

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.

Social Media Mining and Social Network Analysis Emerging Research

Social Media Mining and Social Network Analysis  Emerging Research Book
Author : Xu, Guandong
Publisher : IGI Global
Release : 2013-01-31
ISBN : 1466628073
Language : En, Es, Fr & De

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Book Description :

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.

Analyzing the Strategic Role of Social Networking in Firm Growth and Productivity

Analyzing the Strategic Role of Social Networking in Firm Growth and Productivity Book
Author : Benson, Vladlena,Tuninga, Ronald,Saridakis, George
Publisher : IGI Global
Release : 2016-08-31
ISBN : 1522505601
Language : En, Es, Fr & De

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Book Description :

Social media platforms have emerged as an influential and popular tool in the digital era. No longer limited to just personal use, the applications of social media have expanded in recent years into the business realm. Analyzing the Strategic Role of Social Networking in Firm Growth and Productivity examines the role of social media technology in organizational settings to promote business development and growth. Highlighting a range of relevant discussions from the public and private sectors, this book is a pivotal reference source for professionals, researchers, upper-level students, and academicians.

Mining the Social Web

Mining the Social Web Book
Author : Matthew A. Russell,Mikhail Klassen
Publisher : "O'Reilly Media, Inc."
Release : 2018-12-04
ISBN : 1491973501
Language : En, Es, Fr & De

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Book Description :

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

Analyzing Social Media Data and Web Networks

Analyzing Social Media Data and Web Networks Book
Author : M. Cantijoch,R. Gibson,S. Ward
Publisher : Springer
Release : 2014-11-25
ISBN : 1137276770
Language : En, Es, Fr & De

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Book Description :

As governments, citizens and organizations have moved online there is an increasing need for academic enquiry to adapt to this new context for communication and political action. This adaptation is crucially dependent on researchers being equipped with the necessary methodological tools to extract, analyze and visualize patterns of web activity. This volume profiles the latest techniques being employed by social scientists to collect and interpret data from some of the most popular social media applications, the political parties' own online activist spaces, and the wider system of hyperlinks that structure the inter-connections between these sites. Including contributions from a range of academic disciplines including Political Science, Media and Communication Studies, Economics, and Computer Science, this study showcases a new methodological approach that has been expressly designed to capture and analyze web data in the process of investigating substantive questions.

Mining the Social Web

Mining the Social Web Book
Author : Matthew A. Russell
Publisher : "O'Reilly Media, Inc."
Release : 2013-10-04
ISBN : 1449368220
Language : En, Es, Fr & De

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Book Description :

How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs. Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit Take advantage of more than two-dozen Twitter recipes, presented in O’Reilly’s popular "problem/solution/discussion" cookbook format The example code for this unique data science book is maintained in a public GitHub repository. It’s designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.

Sentiment Analysis in Social Networks

Sentiment Analysis in Social Networks Book
Author : Federico Pozzi,Elisabetta Fersini,Bing Liu,Enza Messina
Publisher : Morgan Kaufmann Publishers
Release : 2016-10-01
ISBN : 9780128044124
Language : En, Es, Fr & De

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Book Description :

The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking." Sentiment Analysis in Social Networks" begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologiesProvides insights into opinion spamming, reasoning, and social network analysisShows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequencesServes as a one-stop reference for the state-of-the-art in social media analytics Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologiesProvides insights into opinion spamming, reasoning, and social network miningShows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequencesServes as a one-stop reference for the state-of-the-art in social media analytics