找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics; Atsushi Nara,Ming-Hsiang Tsou Book 2021 Springer Natur

[復(fù)制鏈接]
查看: 27701|回復(fù): 53
樓主
發(fā)表于 2025-3-21 19:42:25 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics
編輯Atsushi Nara,Ming-Hsiang Tsou
視頻videohttp://file.papertrans.cn/310/309085/309085.mp4
概述Highlights geospatial research using social media and big data.Introduces methodologies and techniques on how to handle and analyze social media and big data.Exhibits various research examples from in
叢書名稱Human Dynamics in Smart Cities
圖書封面Titlebook: Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics;  Atsushi Nara,Ming-Hsiang Tsou Book 2021 Springer Natur
描述.This book discusses theoretical backgrounds, techniques and methodologies, and applications of the current state-of-the-art human dynamics research utilizing social media and geospatial big data. It describes various forms of social media and big data with location information, theory development, data collection and management techniques, and analytical methodologies to conduct human dynamics research including geographic information systems (GIS), spatiotemporal data analytics, text mining and semantic analysis, machine learning, trajectory data analysis, and geovisualization. The book also covers applied interdisciplinary research examples ranging from disaster management, public health, urban geography, and spatiotemporal information diffusion. By providing theoretical foundations, solid empirical research backgrounds, techniques, and methodologies as well as application examples from diverse interdisciplinary fields, this book will be a valuable resource to students, researchers and practitioners who utilize or plan to employ social media and big data in their work..
出版日期Book 2021
關(guān)鍵詞Social Media; Human Dynamics; Spatial and Spatiotemporal Data Analytics; Big Data; Geovisualization; GIS;
版次1
doihttps://doi.org/10.1007/978-3-030-83010-6
isbn_softcover978-3-030-83012-0
isbn_ebook978-3-030-83010-6Series ISSN 2523-7780 Series E-ISSN 2523-7799
issn_series 2523-7780
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics影響因子(影響力)




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics影響因子(影響力)學(xué)科排名




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics網(wǎng)絡(luò)公開度




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics被引頻次




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics被引頻次學(xué)科排名




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics年度引用




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics年度引用學(xué)科排名




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics讀者反饋




書目名稱Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

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

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 21:02:51 | 只看該作者
Theorizing Social Media: A Formalization of the Multilevel Model of Meme Diffusion 2.0 (M3D2.0),iscovered. This essay extends a formative conceptualization of social media communication as meme diffusion into a propositional model, animated largely by evolutionary and attention economy explanatory metaphors. The result is an integrative model formalized in 18 propositions, indicating that mult
板凳
發(fā)表于 2025-3-22 00:43:26 | 只看該作者
地板
發(fā)表于 2025-3-22 05:55:58 | 只看該作者
Research Trends in Social Media/Big Data with the Emphasis on Data Collection and Data Management: prerequisite for Human Dynamics Research utilizing Social Media/Big Data. The ever-changing academic landscape of this field has been characterized by rapid expansion of various applications and dynamic collaboration across multiple disciplines, yielding an increasing number of publications. This ch
5#
發(fā)表于 2025-3-22 09:59:10 | 只看該作者
Similarity Measurement on Human Mobility Data with Spatially Weighted Structural Similarity Index (a variety of data sources, and each describes unique mobility characteristics. Revealing similarity and difference in various data sources facilitates grasping comprehensive human mobility patterns. This study introduces a new method to measure similarities on two origin–destination (OD) matrices by
6#
發(fā)表于 2025-3-22 16:20:38 | 只看該作者
7#
發(fā)表于 2025-3-22 20:12:31 | 只看該作者
Learning Dependence Relationships of Evacuation Decision Making Factors from Tweets,anding how they affect individuals’ evacuation decisions can help emergency response organizations improve evacuation plans and communication strategies. Conventionally, researchers have studied human evacuation behaviors by conducting post-disaster surveys, which could be costly, be?limited by samp
8#
發(fā)表于 2025-3-22 21:25:38 | 只看該作者
Examining Spatiotemporal and Sentiment Patterns of Evacuation Behavior During 2017 Hurricane Harveywledged that a more comprehensive understanding of the evacuation behaviors will significantly mitigate the loss of natural hazards, and can also improve the management process for corresponding agencies. Social media platform with user-generated content provides great potentials in better understan
9#
發(fā)表于 2025-3-23 04:00:42 | 只看該作者
Sentiment Analysis of Social Media Response and Spatial Distribution Patterns on the COVID-19 Outbrlion COVID-19 related tweets classified as fear, anger, and joy in four of Italy’s geographic regions to investigate whether socioeconomic factors and sentiments of tweets shift over the course of the pandemic and when lagged to specific policy shifts before and after the lock-down. The result shows
10#
發(fā)表于 2025-3-23 06:08:59 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-13 23:47
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
磐石市| 攀枝花市| 广汉市| 凤山县| 五常市| 高雄市| 稻城县| 新干县| 阿尔山市| 房山区| 奉化市| 肃北| 乐山市| 滦平县| 建瓯市| 仁化县| 灌南县| 电白县| 尼勒克县| 武陟县| 白银市| 石棉县| 罗定市| 米脂县| 贵州省| 武冈市| 巫溪县| 舟曲县| 九龙城区| 那曲县| 库车县| 成安县| 句容市| 宿松县| 无锡市| 抚松县| 陆良县| 东至县| 新巴尔虎右旗| 肃南| 平度市|