找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Data Science and Social Research; Epistemology, Method N. Carlo Lauro,Enrica Amaturo,Marina Marino Conference proceedings 2017 Springer Int

[复制链接]
查看: 14501|回复: 60
发表于 2025-3-21 18:55:44 | 显示全部楼层 |阅读模式
书目名称Data Science and Social Research
副标题Epistemology, Method
编辑N. Carlo Lauro,Enrica Amaturo,Marina Marino
视频video
概述Applies methods and techniques of data science to the social sciences.Provides extensive examples of new (big) data use in the social sciences.Discusses epistemological consequences of new data on soc
丛书名称Studies in Classification, Data Analysis, and Knowledge Organization
图书封面Titlebook: Data Science and Social Research; Epistemology, Method N. Carlo Lauro,Enrica Amaturo,Marina Marino Conference proceedings 2017 Springer Int
描述.This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. .Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources..This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in acad
出版日期Conference proceedings 2017
关键词data analysis in social sciences; data science and social sciences; data science; new data; textual anal
版次1
doihttps://doi.org/10.1007/978-3-319-55477-8
isbn_softcover978-3-319-55476-1
isbn_ebook978-3-319-55477-8Series ISSN 1431-8814 Series E-ISSN 2198-3321
issn_series 1431-8814
copyrightSpringer International Publishing AG 2017
The information of publication is updating

书目名称Data Science and Social Research影响因子(影响力)




书目名称Data Science and Social Research影响因子(影响力)学科排名




书目名称Data Science and Social Research网络公开度




书目名称Data Science and Social Research网络公开度学科排名




书目名称Data Science and Social Research被引频次




书目名称Data Science and Social Research被引频次学科排名




书目名称Data Science and Social Research年度引用




书目名称Data Science and Social Research年度引用学科排名




书目名称Data Science and Social Research读者反馈




书目名称Data Science and Social Research读者反馈学科排名




单选投票, 共有 0 人参与投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用户组没有投票权限
发表于 2025-3-21 21:50:51 | 显示全部楼层
发表于 2025-3-22 03:47:38 | 显示全部楼层
HDR Spectral Video Measurement Systemcussed the general notion of big data and the meaning of key-concepts such as those of information and data, mainly considering contributions coming from the science and technology studies (STS) and the sociology of quantification. In particular, it is argued the necessary shift from a discrete and
发表于 2025-3-22 07:42:52 | 显示全部楼层
发表于 2025-3-22 09:19:52 | 显示全部楼层
发表于 2025-3-22 16:36:15 | 显示全部楼层
发表于 2025-3-22 18:09:09 | 显示全部楼层
发表于 2025-3-23 00:53:58 | 显示全部楼层
Springer Tracts in Mechanical Engineeringth the aim of identifying the best partition of the objects, described by the best orthogonal linear combinations of the factors, according to the least-squares criterion. This new methodology named multiple correspondence .-means is a useful alternative to the Tandem Analysis in the case of categor
发表于 2025-3-23 02:21:43 | 显示全部楼层
发表于 2025-3-23 09:32:31 | 显示全部楼层
The Computational Creativity Complexclustering technique in order to reduce the sparsity of the matrix without changing the network structure. As an example, we implemented this approach to seek the common meaning of the term sustainability by using an affiliation matrix characterized by a core–periphery structure. The application of
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-23 13:12
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表