Products related to Analysis:
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Social Network Analysis
Incorporating the most important and cutting-edge developments in the field, this bestselling text introduces newcomers to the key theories and techniques of social network analysis and guides more experienced analysts in their own research. New to This Edition:A chapter on data collection, covering a crucial phase of the research processFully updated examples reiterate the continued importance of social network analysis in an increasingly interconnected worldDetailed ‘Further Reading’ sections help you explore the wider literaturePractical exercises including real-world examples of social networks enable you to apply your learningExpanded and brought right up-to-date, this classic text remains the indispensable guide to social network analysis for students, lecturers and researchers throughout the social sciences.
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Social Network Analysis
David Knoke and Song Yang's Social Network Analysis, Third Edition provides a concise introduction to the concepts and tools of social network analysis.The authors convey key material while at the same time minimizing technical complexities.The examples are simple: sets of 5 or 6 entities such as individuals, positions in a hierarchy, political offices, and nation-states, and the relations between them include friendship, communication, supervision, donations, and trade.The new edition reflects developments and changes in practice over the past decade.The authors also describe important recent developments in network analysis, especially in the fifth chapter.Exponential random graph models (ERGMs) are a prime example: when the second edition was published, P* models were the recommended approach for this, but they have been replaced by ERGMs. Finally, throughout the volume, the authors comment on the challenges and opportunities offered by internet and social media data.
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An Analysis of Albert Bandura's Aggression : A Social Learning Analysis
Albert Bandura is the most cited living psychologist, and is regularly named as one of the most influential figures ever to have worked in his field.Much of his reputation stems from the theories and experiments described in his 1973 study Aggression: A Social Learning Analysis – a book that is both a classic of psychological study and a masterclass in the analytical skills central to good critical thinking.Bandura’s central contention is that much human learning is fundamentally social.As children imitate the behavior of those around them, and as their behaviors are reinforced by modelling, they entrench cognitive functions that more or less become part of their core personalities.The experiments that Bandura designed in order to prove his contentions with regard to learned aggressive tendencies show the powers of critical thinking analysis and evaluation at their best.Having set up a play environment for children in which they could be exposed to aggressive behavior (inflicted on a bobo doll), he was able to systematically examine their responses and learned behaviors, working out their functions and understanding the relationships between different aspects of behavior that combined to form a whole.Carefully evaluating at each stage the different extent to which children’s own aggressive behavior was affected by and modelled on what they saw.Bandura produced results that revolutionized psychology’s whole approach to human learning and behavior.
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Graph-Based Social Media Analysis
Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media.It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear algebra, digital media, machine learning, big data analysis, and signal processing.Supplying an overview of graph-based social media analysis, the book provides readers with a clear understanding of social media structure.It uses graph theory, particularly the algebraic description and analysis of graphs, in social media studies. The book emphasizes the big data aspects of social and digital media.It presents various approaches to storing vast amounts of data online and retrieving that data in real-time.It demystifies complex social media phenomena, such as information diffusion, marketing and recommendation systems in social media, and evolving systems.It also covers emerging trends, such as big data analysis and social media evolution. Describing how to conduct proper analysis of the social and digital media markets, the book provides insights into processing, storing, and visualizing big social media data and social graphs.It includes coverage of graphs in social and digital media, graph and hyper-graph fundamentals, mathematical foundations coming from linear algebra, algebraic graph analysis, graph clustering, community detection, graph matching, web search based on ranking, label propagation and diffusion in social media, graph-based pattern recognition and machine learning, graph-based pattern classification and dimensionality reduction, and much more. This book is an ideal reference for scientists and engineers working in social media and digital media production and distribution.It is also suitable for use as a textbook in undergraduate or graduate courses on digital media, social media, or social networks.
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Power : A New Social Analysis
The key to human nature that Marx found in wealth and Freud in sex, Bertrand Russell finds in power.Power, he argues, is man's ultimate goal, and is, in its many guises, the single most important element in the development of any society.Writting in the late 1930s when Europe was being torn apart by extremist ideologies and the world was on the brink of war, Russell set out to found a 'new science' to make sense of the traumatic events of the day and explain those that would follow.The result was Power, a remarkable book that Russell regarded as one of the most important of his long career.Countering the totalitarian desire to dominate, Russell shows how political enlightenment and human understanding can lead to peace - his book is a passionate call for independence of mind and a celebration of the instinctive joy of human life.
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Social Network Analysis : Research Methods
This book introduces the non-specialist reader to the principal ideas, nature and purpose of social network analysis.Social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals achieve their goals.Social network theory maps these relationships between individual actors and has become hugely influential across the social sciences.Assuming no prior knowledge of quantitative sociology, and avoiding technicalities, this book presents the key ideas in context through examples and illustrations.Using a structured approach to understanding work in this area, John Scott signposts further reading and online sources so that readers can develop their knowledge and skills to become practitioners of this research method.A series of Frequently Asked Questions takes the reader through the main objections raised against social network analysis.The new edition updates the overview of the discipline with more recent work and current research in sociology.
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Social Network Analysis : Methods and Examples
Social Network Analysis: Methods and Examples prepares social science students to conduct their own social network analysis (SNA) by covering basic methodological tools along with illustrative examples from various fields.This innovative book takes a conceptual rather than a mathematical approach as it discusses the connection between what SNA methods have to offer and how those methods are used in research design, data collection, and analysis.Four substantive applications chapters provide examples from politics, work and organizations, mental and physical health, and crime and terrorism studies.
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Semantic Network Analysis in Social Sciences
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.
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Similar search terms for Analysis:
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Is source analysis the same as text analysis?
Source analysis and text analysis are related but not the same. Source analysis involves examining the origin, context, and credibility of a source, while text analysis focuses on interpreting and understanding the content of a text itself. Source analysis helps determine the reliability and bias of a source, while text analysis delves into the meaning, structure, and language used in a text. Both are important in research and critical thinking, but they serve different purposes in analyzing information.
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Is dialog analysis the same as scene analysis?
Dialog analysis and scene analysis are not the same, although they are related. Dialog analysis focuses specifically on the spoken interactions between characters, examining the content, tone, and subtext of the conversations. On the other hand, scene analysis encompasses a broader view of the entire scene, including the setting, actions, and non-verbal communication in addition to the dialog. While dialog analysis is a part of scene analysis, scene analysis includes a more comprehensive examination of all elements within a particular scene.
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What is the analysis of the semen analysis?
The analysis of a semen analysis typically includes evaluating the volume of semen, sperm count, sperm motility, and sperm morphology. The volume of semen provides information about the amount of fluid produced by the male reproductive system. Sperm count measures the number of sperm present in the semen, while sperm motility assesses the movement and speed of the sperm. Sperm morphology examines the shape and structure of the sperm, looking for abnormalities that may affect fertility. Overall, the analysis provides important information about a man's fertility potential and can help identify any potential issues with sperm quality or quantity.
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How can one improve text comprehension in social science analysis?
One can improve text comprehension in social science analysis by actively engaging with the text through techniques such as annotating, summarizing, and asking questions. It is also important to consider the context and background of the text, as well as the author's perspective and potential biases. Additionally, discussing the text with others and seeking out different perspectives can help deepen understanding and improve comprehension in social science analysis. Finally, practicing critical thinking skills and being open to new ideas and interpretations can also enhance text comprehension in this field.
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What is the difference between a textual analysis, a scene analysis, and a narrative analysis?
A textual analysis focuses on the language and structure of a written text, examining the use of literary devices, themes, and symbolism. A scene analysis, on the other hand, zooms in on a specific segment of a film or play, analyzing the visual and auditory elements, character interactions, and the overall impact of the scene on the narrative. Narrative analysis, meanwhile, looks at the broader story structure, character development, and the way the plot unfolds over the course of the entire text. Each type of analysis offers a unique perspective on the text and allows for a deeper understanding of its meaning and impact.
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What is the difference between Analysis and Higher Analysis?
Analysis is the branch of mathematics that deals with limits, continuity, derivatives, integrals, and infinite series. It is a fundamental area of mathematics that is essential for understanding calculus and other advanced mathematical concepts. Higher Analysis, on the other hand, refers to more advanced topics within the field of analysis, such as functional analysis, complex analysis, and harmonic analysis. These areas delve deeper into the study of functions, spaces, and structures, and often involve more abstract and complex mathematical techniques.
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Is source analysis the same as factual text analysis?
Source analysis and factual text analysis are related but not the same. Source analysis involves evaluating the credibility, bias, and perspective of the source of information, while factual text analysis focuses on examining the content of the text for accuracy and reliability of the information presented. Source analysis helps determine the trustworthiness of the information, while factual text analysis assesses the content itself. Both are important in critically evaluating information, but they involve different aspects of analysis.
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What is the difference between Analysis and Advanced Analysis?
Analysis typically involves examining data or information to understand its components, structure, and meaning. Advanced Analysis, on the other hand, involves a more in-depth and complex examination of data using sophisticated techniques and tools. It often requires a higher level of expertise and specialized knowledge to uncover deeper insights, patterns, and trends that may not be easily visible through traditional analysis methods. Advanced Analysis may also involve predictive modeling, machine learning, or other advanced statistical techniques to extract valuable insights from data.
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