Big Data Topologia E Investigacion Social
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Author | : Fernando Conde Gutiérrez del Álamo |
Publisher | : |
Total Pages | : 0 |
Release | : 2023 |
Genre | : |
ISBN | : 9788436278651 |
Big Data, topología e investigación social, orientado para los estudiantes y para los investigadores universitarios y empresariales que trabajan en el ámbito de las ciencias sociales, pretende ser un texto introductorio al debate sobre los usos del big data y de la inteligencia artificial en la investigación social y sus repercusiones en las metodologías y los estilos de trabajo de los investigadores en ciencias sociales. El libro aborda las distintas posiciones que unas y otras corrientes teóricas han desarrollado sobre el big data y la inteligencia artificial. Propone una caracterización del big data en el conjunto de las metodologías de la investigación social y, basándose en la larga experiencia de investigación del autor, desarrolla una aproximación al big data que respetando su singularidad sugiere, en el caso de la investigación con redes complejas, el uso de la topología como lenguaje de análisis y de acercamiento a otras líneas de investigación.
Author | : Robles, José Manuel |
Publisher | : CIS |
Total Pages | : 304 |
Release | : 2020-10-29 |
Genre | : Social Science |
ISBN | : 8474768438 |
La revolución digital ha generado un conjunto de transformaciones de gran relevancia social, política, económica y cultural. En el ámbito de la investigación social, la emergencia de dispositivos que rápida y constantemente recogen y almacenan nuestras opiniones, hábitos de consumo, movilidad, etc., ha supuesto un profundo reajusteen los procesos de análisis, así como en las metodologías y herramientas utilizadas. Big data es el término usado para designar este tipo de datos, así como las técnicas empleadas para extraer información de ellos. Dichas técnicas y, por lo tanto, sus resultados han sido durante los últimos años patrimonio de estadísticos, matemáticos y científicos de datos. Este manual, por el contrario, pretende ser un instrumento para que los científicos sociales conozcan el big data y estén en disposición de formar parte de grupos de investigación multidisciplinares cuyo objetivo sea conocer mejor el mundo en el que vivimos a través de las lentes que nos facilitan estos datos masivos y digitales.
Author | : Bilal Abu-Salih |
Publisher | : Springer Nature |
Total Pages | : 218 |
Release | : 2021-03-10 |
Genre | : Business & Economics |
ISBN | : 9813366524 |
This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.
Author | : Mehmet Kaya |
Publisher | : Springer |
Total Pages | : 254 |
Release | : 2018-05-10 |
Genre | : Social Science |
ISBN | : 3319781960 |
This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
Author | : Jordi Morales i Gras |
Publisher | : Editorial UOC |
Total Pages | : 124 |
Release | : 2022-02-28 |
Genre | : Language Arts & Disciplines |
ISBN | : 8491809260 |
Un hacker es alguien con la capacidad de versionar y subvertir una temática u objeto, agarrándolo y dándole otra función. Lo que la ciencia social necesita hoy son hackers que actúen desde la autonomía y desde la soberanía tecnológica. El hackeo de la ciencia social es una necesidad, en tanto que las condiciones para su construcción, comenzando por los instrumentos de registro de los datos sociales, se han visto drásticamente transformadas durante los últimos años, afectando enormemente la capacidad y la calidad de la inferencia científico-social y alterando las condiciones para la constitución sociohistórica de individuos y sociedades.
Author | : Mehmet Çakırtaş |
Publisher | : Springer Nature |
Total Pages | : 246 |
Release | : 2021-07-05 |
Genre | : Mathematics |
ISBN | : 3030670449 |
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.
Author | : My T. Thai |
Publisher | : Chapman and Hall/CRC |
Total Pages | : 0 |
Release | : 2016-01-15 |
Genre | : Business & Economics |
ISBN | : 9781498726849 |
The ultimate objective of this book is to provide the academic and industrial communities with an in-depth introduction to the recent advances in development, theory, and impacts of Big Data, tailored to applications in complex and social networks. Specifically, the book focuses on how to retrieve, store, manipulate and analyze data and how to develop new tools and techniques to study and visualize massive datasets in the domain of complex and social networks.
Author | : Mrutyunjaya Panda |
Publisher | : CRC Press |
Total Pages | : 316 |
Release | : 2018-12-12 |
Genre | : Business & Economics |
ISBN | : 1351622595 |
Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.
Author | : Joaquín Castillo de Mesa |
Publisher | : |
Total Pages | : 234 |
Release | : 2017 |
Genre | : |
ISBN | : 9788491772705 |
Author | : Ian Foster |
Publisher | : |
Total Pages | : |
Release | : 2017 |
Genre | : SOCIAL SCIENCE |
ISBN | : 9781315320250 |