Challenges Of Computational Social Science Analysis With Nlp Methods


Challenges Of Computational Social Science Analysis With Nlp Methods
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Opportunities And Challenges For Computational Social Science Methods


Opportunities And Challenges For Computational Social Science Methods
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Author : Abanoz, Enes
language : en
Publisher: IGI Global
Release Date : 2022-03-18

Opportunities And Challenges For Computational Social Science Methods written by Abanoz, Enes and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-18 with Social Science categories.


We are living in a digital era in which most of our daily activities take place online. This has created a big data phenomenon that has been subject to scientific research with increasingly available tools and processing power. As a result, a growing number of social science scholars are using computational methods for analyzing social behavior. To further the area, these evolving methods must be made known to sociological research scholars. Opportunities and Challenges for Computational Social Science Methods focuses on the implementation of social science methods and the opportunities and challenges of these methods. This book sheds light on the infrastructure that should be built to gain required skillsets, the tools used in computational social sciences, and the methods developed and applied into computational social sciences. Covering topics like computational communication, ecological cognition, and natural language processing, this book is an essential resource for researchers, data scientists, scholars, students, professors, sociologists, and academicians.



Handbook Of Computational Social Science For Policy


Handbook Of Computational Social Science For Policy
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Author : Eleonora Bertoni
language : en
Publisher: Springer Nature
Release Date : 2023-01-23

Handbook Of Computational Social Science For Policy written by Eleonora Bertoni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-23 with Computers categories.


This open access handbook describes foundational issues, methodological approaches and examples on how to analyse and model data using Computational Social Science (CSS) for policy support. Up to now, CSS studies have mostly developed on a small, proof-of concept, scale that prevented from unleashing its potential to provide systematic impact to the policy cycle, as well as from improving the understanding of societal problems to the definition, assessment, evaluation, and monitoring of policies. The aim of this handbook is to fill this gap by exploring ways to analyse and model data for policy support, and to advocate the adoption of CSS solutions for policy by raising awareness of existing implementations of CSS in policy-relevant fields. To this end, the book explores applications of computational methods and approaches like big data, machine learning, statistical learning, sentiment analysis, text mining, systems modelling, and network analysis to different problems in the social sciences. The book is structured into three Parts: the first chapters on foundational issues open with an exposition and description of key policymaking areas where CSS can provide insights and information. In detail, the chapters cover public policy, governance, data justice and other ethical issues. Part two consists of chapters on methodological aspects dealing with issues such as the modelling of complexity, natural language processing, validity and lack of data, and innovation in official statistics. Finally, Part three describes the application of computational methods, challenges and opportunities in various social science areas, including economics, sociology, demography, migration, climate change, epidemiology, geography, and disaster management. The target audience of the book spans from the scientific community engaged in CSS research to policymakers interested in evidence-informed policy interventions, but also includes private companies holding data that can be used to study social sciences and are interested in achieving a policy impact.



Computational Thinking And Social Science


Computational Thinking And Social Science
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Author : Matti Nelimarkka
language : en
Publisher: SAGE
Release Date : 2022-11-30

Computational Thinking And Social Science written by Matti Nelimarkka and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Social Science categories.


Whilst providing a fundamental understanding of computational social science, this book delves into the tools and techniques used to build familiarity with programming and gain context into how, why and when they are introduced. The overall focus is on helping you understand and design computational social science research, alongside delving into hands-on coding and technical instruction. Key features include: Further reading Exercises accompanied by sample code Programming examples in Scratch, Python and R Key concepts Chapter summaries With experience in course design and teaching, Matti Nelimarkka has a deep understanding of learning techniques within computational social sciences, with the main aim of blending researching, thinking and designing together to gain a grounded foundation for coding, programming, methodologies and key concepts.



Computational Social Science


Computational Social Science
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Author : R. Michael Alvarez
language : en
Publisher: Cambridge University Press
Release Date : 2016-03-07

Computational Social Science written by R. Michael Alvarez and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-07 with Political Science categories.


Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social science - in academia, government, and the private sector - while highlighting current trends, challenges, and new directions. Thus, Computational Social Science showcases the innovative methodological tools being developed and applied by leading researchers in this new field. The book shows how academics and the private sector are using many of these tools to solve problems in social science and public policy.



Handbook Of Computational Social Science Volume 1


Handbook Of Computational Social Science Volume 1
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Author : Uwe Engel
language : en
Publisher: Routledge
Release Date : 2021-11-10

Handbook Of Computational Social Science Volume 1 written by Uwe Engel and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-10 with Computers categories.


The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. It covers a range of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field but also encourages growth in new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientifi c and engineering sectors.



Pathways Between Social Science And Computational Social Science


Pathways Between Social Science And Computational Social Science
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Author : Tamás Rudas
language : en
Publisher: Springer Nature
Release Date : 2021-01-22

Pathways Between Social Science And Computational Social Science written by Tamás Rudas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-22 with Social Science categories.


This volume shows that the emergence of computational social science (CSS) is an endogenous response to problems from within the social sciences and not exogeneous. The three parts of the volume address various pathways along which CSS has been developing from and interacting with existing research frameworks. The first part exemplifies how new theoretical models and approaches on which CSS research is based arise from theories of social science. The second part is about methodological advances facilitated by CSS-related techniques. The third part illustrates the contribution of CSS to traditional social science topics, further attesting to the embedded nature of CSS. The expected readership of the volume includes researchers with a traditional social science background who wish to approach CSS, experts in CSS looking for substantive links to more traditional social science theories, methods and topics, and finally, students working in both fields.



Emerging Research Challenges And Opportunities In Computational Social Network Analysis And Mining


Emerging Research Challenges And Opportunities In Computational Social Network Analysis And Mining
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Author : Nitin Agarwal
language : en
Publisher: Springer
Release Date : 2018-09-17

Emerging Research Challenges And Opportunities In Computational Social Network Analysis And Mining written by Nitin Agarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-17 with Social Science categories.


The contributors in this book share, exchange, and develop new concepts, ideas, principles, and methodologies in order to advance and deepen our understanding of social networks in the new generation of Information and Communication Technologies (ICT) enabled by Web 2.0, also referred to as social media, to help policy-making. This interdisciplinary work provides a platform for researchers, practitioners, and graduate students from sociology, behavioral science, computer science, psychology, cultural studies, information systems, operations research and communication to share, exchange, learn, and develop new concepts, ideas, principles, and methodologies. Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining will be of interest to researchers, practitioners, and graduate students from the various disciplines listed above. The text facilitates the dissemination of investigations of the dynamics and structure of web based social networks. The book can be used as a reference text for advanced courses on Social Network Analysis, Sociology, Communication, Organization Theory, Cyber-anthropology, Cyber-diplomacy, and Information Technology and Justice.



Text As Data


Text As Data
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Author : Justin Grimmer
language : en
Publisher: Princeton University Press
Release Date : 2022-03-29

Text As Data written by Justin Grimmer and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-29 with Computers categories.


A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry



Methods And Instruments In The Study Of Meaning Making


Methods And Instruments In The Study Of Meaning Making
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Author : Sergio Salvatore
language : en
Publisher: Springer Nature
Release Date : 2023-02-24

Methods And Instruments In The Study Of Meaning Making written by Sergio Salvatore and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-24 with Social Science categories.


This volume develops a theoretical framework for the modelling of meaning-making and cultural processes as crucial to the scientific study of contemporary complex societies. It focuses on the methodological and empirical aspects of the analysis of culture and its dynamics that could be applied to policymaking and to the understanding of social phenomena. It covers culture-based segmentation, ad hoc survey instruments like the VOC and PROSERV questionnaires, discourse flow analysis, the Homogenization of Classification Functions Measurement, and others. It also presents a detailed discussion of the methodology of cultural analysis in contexts of health and education. The volume showcases a top-down approach by including quantitative methods and/or automatized or semi-automatized procedures, and at the same time supports a hermeneutic, bottom-up, abductive approach, focused on the situated dynamics of meaning-making. It provides insights from cultural studies, social statistics, social policy, and research methodology in the social sciences. This is a useful resource for academics involved in studying cultural dynamics and for policy-oriented researchers and decision-makers who are interested in cultural dimensions of the design, implementation and reception of public policies.



Handbook Of Computational Social Science Volume 2


Handbook Of Computational Social Science Volume 2
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Author : Uwe Engel
language : en
Publisher: Taylor & Francis
Release Date : 2021-11-10

Handbook Of Computational Social Science Volume 2 written by Uwe Engel and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-10 with Computers categories.


The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This second volume focuses on foundations and advances in data science, statistical modeling, and machine learning. It covers a range of key issues, including the management of big data in terms of record linkage, streaming, and missing data. Machine learning, agent-based and statistical modeling, as well as data quality in relation to digital trace and textual data, as well as probability, non-probability, and crowdsourced samples represent further foci. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors.