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

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倔強一點

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

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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

暗諷

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

Anticonvulsants

Anticonvulsants

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

Engulf

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

污穢

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

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