DFG, SPP 1894/1 – Volunteered Geographic Information

Project Lead
Team Member

Spatial Correlations in Social Media Data

Identification and Quantification of Spatial Correlation Structures in Georeferenced Twitter Feeds

Social media feeds are one of the growing numbers of sources of volunteered geographic information. Thereby, over recent years, this kind of data has proven to be a rich source of information for many areas of research. This proposal aims to contribute methodological advancements, whereby we focus on Twitter data. Specifically, we aim to explore novel ways to derive spatial correlation structures within social media feeds. Our work builds upon the mature theory of spatial autocorrelation, which is the traditional way of measuring spatial structure.

The first research question is concerned with integrating the theory of spatial autocorrelation with the geometric stochasticity of tweets. The latter is typically investigated by means of stochastic geometry. We aim to combine principles from both fields in order to derive more accurate correlation structures within tweets. In a first step we investigate the effect of the stochastic geometries on spatial autocorrelation measures. This includes point pattern modelling and a Monte Carlo simulation study. That investigation will provide insights regarding a better interpretation of autocorrelation results. Moreover, the gained knowledge allows detailed insights into the variability of inter-tweet correlations of certain social activities. After this exploratory study, we investigate a measure of spatial autocorrelation that acknowledges the stochasticity of the underlying geometric structure and is thus able to obtain meaningful patterns within social media data.

Secondly we investigate the mutually overlapping character of phenomena that are reflected within the tweets. This overlap is caused by the autonomous behaviour of the users, which report about multiple phenomena simultaneously in space and time. We aim to explore ways of separating relevant tweets from non-relevant ones. This is done by means of Dempster-Shafer theory and Dirichlet processes. The challenge thereby is to disentangle the geometrically overlapping neighbourhoods. In a second step we expand spatial autocorrelation measures towards acknowledging this overlapping character by means of partial autocorrelation functions. This will prevent mixing different phenomena and leads to realistic dependency structures.

While the first two packages focus on the point level, the third aspect addresses suitable aggregation strategies. These strategies involve traditional clustering techniques and indices from point pattern analysis. This allows analysing dependencies between different kinds of compound social activities. Further, aggregating tweets allows investigating the relationship of social processes towards their immediate surroundings. This will be a second step of this work package.

Overall, our research will enable for gaining an increased and detailed understanding of social activities and their respective spatial mechanisms through improved methods allowing to analyse representations of these within socio-technical systems.

25.06.2019 11:12
Methodological aspects of the spatial analysis of geosocial media feeds: from locations towards places

A new journal article about Methodological aspects of the spatial analysis of geosocial media feeds: from locations towards places has just been published in gis.science Vol 2 2019. It covers some main aspects and findings of the PhD Thesis of our team member Rene Westerholt (now at Warwick UK) and relates those to the analysis of place in [...]

05.06.2019 15:22
Understanding human mobility from social media data for epidemic surveillance in urban environment

Vector-born diseases – such as Malaria, Dengue or Zika are serious health hazards in tropical regions. The outbreaks show high temporal and spatial variability. For example, the number of dengue cases in the state of São Paulo increased by 2,124% in the first 11 weeks of 2019 (up to March 16, 229,064 cases were reported), [...]

19.10.2018 09:54
An exploration of the interaction between urban human activities and daily traffic conditions: A case study of Toronto, Canada

Understanding how citizens interact with transportation system is a key to solving a variety of urban issues in general and traffic congestion in particular. Recently, scholars have put efforts on the pertinent work ranging from developing traffic predictors to understanding human mobility and activity patterns. Multiple types of data have been used, of which crowdsourced [...]

04.06.2018 21:45
Successful DFG VGIscience Collaborative Research Week in Heidelberg

Last week about 30 scientists from different insitutions from all across Germany came together in Heidelberg to conduct collaborative research. The research week is the result of an intense collaboration within the DFG Priority Programme VGIscience, which deals with the following topics Information Retrieval and Analysis of VGI: • information extraction (space, time, semantics) • data aggregation and [...]

25.04.2018 15:48
Coupling maximum entropy modeling with geotagged social media data to determine the geographic distribution of tourists

Modeling the geographic distribution of tourists at a tourist destination is crucial when it comes to enhancing the destination’s resilience to disasters and crises, as it enables the efficient allocation of limited resources to precise geographic locations. Seldom have existing studies explored the geographic distribution of tourists through understanding the mechanisms behind it. A recently [...]

20.04.2018 08:05
Colloquium on Micro Diagrams for Geovisual Analysis of Point Datasets

We cordially invite everybody interested to our next open GIScience colloquium talk The speaker is Mathias Gröbe Technical University of Dresden, Department of Geosciences, Institute of Cartography When: Monday 23.04.2018, 14:15 Where: INF 348, room 015 (Institute of Geography, Heidelberg University) Micro Diagrams: A Multi-Scale Approach for Geovisual Analysis of Categorised Point Datasets Location-based social media from different platforms such as Twitter and [...]

17.03.2018 15:21
POI/ROI Discovery using Flickr geotagged photos

In the era of big data, ubiquitous Flickr geotagged photos have opened a considerable opportunity for discovering valuable geographic information. Point of interest (POI) and region of interest (ROI) are significant reference data that are widely used in geospatial applications. A recently published study (Kuo et al 2018) study aims to develop an efficient method [...]

28.12.2017 13:24
Most Cited Article in Transactions in GIS is on systematic literature review on spatiotemporal analyses of Twitter data

The following article is the Top Most Cited Article of the last two years in [...]

16.12.2017 09:25
GIScience Colloquium Talk on Reconstructing Travelers Semantic Trajectories

we cordially invite everybody interested to our next open GIScience colloquium talk Travel History: Reconstructing Travelers Semantic Trajectories Based on Heterogeneous Social Footprints Amon Veiga Santana Heidelberg University, Institute of Geography, GIScience Research Group Time and date: Mon, December 18, 2:15 pm Venue: INF 348, Room 015, Department of Geography, Heidelberg University Travel specialized services on the web have increased their sociability [...]

08.12.2017 08:52
GIScience Colloquium Talk on Geospatial Visual Analytics Applications

we cordially invite everybody interested to our next open GIScience colloquium talk Geospatial Visual Analytics Applications for Predictive Analysis Dr. Alexandra Diehl University of Konstanz, Department of Computer and Information Science, Data Analysis and Visualization Time and date: Mon, December 11, 2:15 pm Venue: INF 348, Room 015, Department of Geography, Heidelberg University In this talk, the speaker will introduce her [...]

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