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Innovation in hyperlink and social media networks: Comparing connection strategies of innovative companies in hyperlink and social media networks

Journal Article

This paper seeks to unveil how (geospatial) connection strategies associated with business innovation, differ between geolocated social media and hyperlink company networks. Thereby, we provide a first step towards understanding connection strategies of...

Assessing Reliability of Chinese Geotagged Social Media Data for Spatiotemporal Representation of Human Mobility

Journal Article

Understanding the space-time dynamics of human activities is essential in studying human security issues such as climate change impacts, pandemic spreading, or urban sustainability. Geotagged social media posts provide an open and space-time continuous...

Modeling the social media information network across space

Event

Presentation by Dr. Yilan Xu, University of Illinois. View the presentation slides | A video recording of the presentation is available by contacting the CGA. Talk Abstract: This paper takes a data-driven approach to model how social media information...

Digital Timescapes in Urban Public Space: How Social Media Folds Pasts into Presents

Event

Presentation by Dr. Tabea Bork-Hüffer | Room K354, CGIS Knafel | Zoom link to register to attend virtually. | To request to view a video recording of this presentation, please use this form to contact us. Abstract: Digital representations of space, place...

Well-being, Emotion, Network: Geo-spatial Trackers of Unobservable Human Attributes on Social Media

Event

Presentation by Yichun Fan View the slides and the recording of this presentation. Abstract Human behaviors and performances are largely determined by unobservable human attributes, which hinder the progress of social and behavioral science. The...

Use of Social Media data to study Climate Change

Page

Harvard CGA joined forces with MIT SUL in 2021 to use social media data to study the effects of climate change on people’s well being. To achieve this objective, we developed the Twitter Sentiment Global Index (TSGI) dataset, an open dataset for...

Bridging the Gap: A Case Study of Integrating Social Media Big Data with Geography

Event

Integrating social media data with geography can offer great potential for understanding the urban dynamics in real-time. However, traditional GIS systems are limited in processing large-scale datasets. The objective of this work is to develop methods to...

HUMAN+ - Humanitarian Safety through Social Media based Refugee Flows

Event

By: Bernd Resch Abstract: The intensified migratory movements of the last few years are increasingly posing major challenges to authorities, municipalities, relief organizations and NGOs. Particularly, appropriate reception, transfer, supply and...

Spatiotemporal Network Analysis of Cities in the Belt and Road Initiative Countries based on Social Media Mobility Index

Event

AAG 2023 Annual Meeting Authors: Lingbo Liu, Harvard University Xiaokang Fu, Harvard University Abstract The ongoing spread of COVID-19, the war in Ukraine and the intensification of extreme climate events around the world are changing the world, which is...

Decision support for parks and protected areas: Leveraging big data to estimate visitation & examine visitor behavior

Event

View the slides ( PDF ). Listen to the audio ( MP3 ). Abstract Tourism practitioners have long sought robust protected area visitation estimates. US federal agencies charged with managing protected areas have often leveraged unstandardized methods to...

Spatiotemporal Innovation Workshop :Social Media Sentiment Analysis

News

This workshop will cover all aspects sentiment analysis and use of the KNIME analytical platform. The workshop will be held November 28, 29, and December 1. Read more and apply for the workshop.

Identifying Disaster Impacted Areas with Machine Learning and Geospatial Analysis Using Twitter Data

Event

By Clemens Havas, University of Salzburg Abstract: Emergency management relies on up-to-date information about the impact of a disaster in an area. However, current emergency systems rely on data sources that do not provide a complete geospatial and...