Detecting social media users based on pedestrian networks and neighborhood attributes : an observational study

Masias, Victor H. LSF; Hecking, Tobias GND; Crespo, Fernando; Hoppe, H. Ulrich GND

This paper proposes a methodological approach to explore the ability to detect social media users based on pedestrian networks and neighborhood attributes. We propose the use of a detection function belonging to the Spatial Capture–Recapture (SCR) which is a powerful analytical approach for detecting and estimating the abundance of biological populations. To test our approach, we created a set of proxy measures for the importance of pedestrian streets as well as neighborhood attributes. The importance of pedestrian streets was measured by centrality indicators. Additionally, proxy measures of neighborhood attributes were created using multivariate analysis of census data. A series of candidate models were tested to determine which attributes are most important for detecting social media users. The results of the analysis provide information on which attributes of the city have promising potential for detecting social media users. Finally, the main results and findings, limitations and extended use of the proposed methodological approach are discussed.

Cite

Citation style:
Masias, V.H., Hecking, T., Crespo, F., Hoppe, H.U., 2019. Detecting social media users based on pedestrian networks and neighborhood attributes: an observational study. https://doi.org/10.1007/s41109-019-0222-4
Could not load citation form.

Rights

License Holder:

© The Author(s). 2019

Use and reproduction:
This work may be used under a
CC BY 4.0 LogoCreative Commons Attribution 4.0 License (CC BY 4.0)
.

Export