Semantic Network Analysis in Social Sciences
Semantic Network Analysis in Social Sciences

Author: Elad Segev

Publisher: Routledge

Published: 2021-11-29

Total Pages: 223

ISBN-13: 1000471918

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Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases. Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It is one of the developing, cutting-edge methods to organize, identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews. Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts.

Semantic Network Analysis
Semantic Network Analysis

Author: Wouter van Atteveldt

Publisher:

Published: 2008

Total Pages: 256

ISBN-13:

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This books describes a number of techniques that have been developed to facilitate Semantic Network Analysis. It describes techniques to automatically extract networks using co-occurrence, grammatical analysis, and sentiment analysis using machine learning. Additionally, it describes techniques to represent the extracted semantic networks and background knowledge about the actors and issues in the network, using Semantic Web techniques to deal with multiple issue categorisations and political roles and functions that shift over time. It shows how this combined network of message content and background knowledge can be queried and visualized to make it easy to answer a variety of research questions. Finally, this book describes the AmCAT infrastructure and iNet coding program for that have been developed to facilitate managing large automatic and manual content analysis projects.

Social Networks and the Semantic Web
Social Networks and the Semantic Web

Author: Peter Mika

Publisher: Springer Science & Business Media

Published: 2007-10-23

Total Pages: 237

ISBN-13: 0387710019

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Social Networks and the Semantic Web offers valuable information to practitioners developing social-semantic software for the Web. It provides two major case studies. The first case study shows the possibilities of tracking a research community over the Web. It reveals how social network mining from the web plays an important role for obtaining large scale, dynamic network data beyond the possibilities of survey methods. The second case study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies.

Sentiment Analysis in Social Networks
Sentiment Analysis in Social Networks

Author: Federico Alberto Pozzi

Publisher: Morgan Kaufmann

Published: 2016-10-06

Total Pages: 286

ISBN-13: 0128044381

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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 methodologies - Provides insights into opinion spamming, reasoning, and social network analysis - Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves 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 methodologies - Provides insights into opinion spamming, reasoning, and social network mining - Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics

Social Network Analysis
Social Network Analysis

Author: Mohammad Gouse Galety

Publisher: John Wiley & Sons

Published: 2022-05-24

Total Pages: 260

ISBN-13: 1119836239

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SOCIAL NETWORK ANALYSIS As social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose. Social network analysis is the solicitation of network science on social networks, and social occurrences are denoted and premeditated by data on coinciding pairs as the entities of opinion. The book features: Social network analysis from a computational perspective using python to show the significance of fundamental facets of network theory and the various metrics used to measure the social network. An understanding of network analysis and motivations to model phenomena as networks. Real-world networks established with human-related data frequently display social properties, i.e., patterns in the graph from which human behavioral patterns can be analyzed and extracted. Exemplifies information cascades that spread through an underlying social network to achieve widespread adoption. Network analysis that offers an appreciation method to health systems and services to illustrate, diagnose, and analyze networks in health systems. The social web has developed a significant social and interactive data source that pays exceptional attention to social science and humanities research. The benefits of artificial intelligence enable social media platforms to meet an increasing number of users and yield the biggest marketplace, thus helping social networking analysis distribute better customer understanding and aiding marketers to target the right customers. Audience The book will interest computer scientists, AI researchers, IT and software engineers, mathematicians.

Social Networks: Analysis and Case Studies
Social Networks: Analysis and Case Studies

Author: Şule Gündüz-Öğüdücü

Publisher: Springer

Published: 2014-07-11

Total Pages: 266

ISBN-13: 3709117976

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The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many opportunities in different application domains. Forming a bridge between theory and applications makes this work appealing to both academics and practitioners as well as graduate students.

Why Context Matters
Why Context Matters

Author: Thomas Friemel

Publisher: Springer Science & Business Media

Published: 2008-11-06

Total Pages: 172

ISBN-13: 3531911848

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In the last few years there has been a growing interest in using computers not only for quantitative but also for qualitative content analyses of various kinds of texts and unstructured interviews (Fielding and Lee 1993, Kelle 1998, Kuckartz 2001, Miles and Huberman 2005, Lewins and Silver 2007). This trend has given rise to the development of new software products such as MAXqda, NVivo, NUD. IST, and ATLAS. ti, which can be used for automatic coding, text retrieval, hyp- linking of related text segments, etc. Some of these programs such as ATLAS. ti or MAXqda even allow to represent the results of qualitative content analyses in graphical form as semantic networks of coded texts (Sowa 1984: 76 ff. , Lewins and Silver 2007: 179 ff. ). Such networks consist of 1. text segments or so-called quotations, which generally constitute a n- overlapping partition of the analyzed text corpus, 2. codes, which are classificatory attributes of the mentioned text segments, 3. links, which are the result of the content analytic coding and describe the attribute relations between the mentioned codes and quotations. Minestrone Soup Non-Eggs Ticinese Leek soup White wine Vegetables Romandie Figure 1: An example of a semantic network of a coded text: soup recipes from Latin Switzer- 1 land Fig.

The Sage Handbook of Social Network Analysis
The Sage Handbook of Social Network Analysis

Author: John McLevey

Publisher: SAGE Publications Limited

Published: 2023-10-01

Total Pages: 951

ISBN-13: 152961466X

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This new edition of The Sage Handbook of Social Network Analysis builds on the success of its predecessor, offering a comprehensive overview of social network analysis produced by leading international scholars in the field. Brand new chapters provide both significant updates to topics covered in the first edition, as well as discussing cutting edge topics that have developed since, including new chapters on: · General issues such as social categories and computational social science; · Applications in contexts such as environmental policy, gender, ethnicity, cognition and social media and digital networks; · Concepts and methods such as centrality, blockmodeling, multilevel network analysis, spatial analysis, data collection, and beyond. By providing authoritative accounts of the history, theories and methodology of various disciplines and topics, the second edition of The SAGE Handbook of Social Network Analysis is designed to provide a state-of-the-art presentation of classic and contemporary views, and to lay the foundations for the further development of the area. PART 1: GENERAL ISSUES PART 2: APPLICATIONS PART 3: CONCEPTS AND METHODS

Encyclopedia of Social Network Analysis and Mining
Encyclopedia of Social Network Analysis and Mining

Author: Reda Alhajj

Publisher: Springer

Published: 2018-05-02

Total Pages: 0

ISBN-13: 9781493971305

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The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and applications to data mining. The second edition of ESNAM is a truly outstanding reference appealing to researchers, practitioners, instructors and students (both undergraduate and graduate), as well as the general public. This updated reference integrates all basics concepts and research efforts under one umbrella. Coverage has been expanded to include new emerging topics such as crowdsourcing, opinion mining, and sentiment analysis. Revised content of existing material keeps the encyclopedia current. The second edition is intended for college students as well as public and academic libraries. It is anticipated to continue to stimulate more awareness of social network applications and research efforts. The advent of electronic communication, and in particular on-line communities, have created social networks of hitherto unimaginable sizes. Reflecting the interdisciplinary nature of this unique field, the essential contributions of diverse disciplines, from computer science, mathematics, and statistics to sociology and behavioral science, are described among the 300 authoritative yet highly readable entries. Students will find a world of information and insight behind the familiar façade of the social networks in which they participate. Researchers and practitioners will benefit from a comprehensive perspective on the methodologies for analysis of constructed networks, and the data mining and machine learning techniques that have proved attractive for sophisticated knowledge discovery in complex applications. Also addressed is the application of social network methodologies to other domains, such as web networks and biological networks.

Mixed Methods Social Networks Research
Mixed Methods Social Networks Research

Author: Silvia Domínguez

Publisher: Cambridge University Press

Published: 2014-06-30

Total Pages: 407

ISBN-13: 1139992244

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This edited volume demonstrates the potential of mixed-methods designs for the research of social networks and the utilization of social networks for other research. Mixing methods applies to the combination and integration of qualitative and quantitative methods. In social network research, mixing methods also applies to the combination of structural and actor-oriented approaches. The volume provides readers with methodological concepts to guide mixed-methods network studies with precise research designs and methods to investigate social networks of various sorts. Each chapter describes the research design used and discusses the strengths of the methods for that particular field and for specific outcomes.