An Advanced Systematic Literature Review on Spatiotemporal Analyses of Twitter Data

Recently an Advanced Systematic Literature Review on Spatiotemporal Analyses of Twitter Data has been conducted and the results have been published online as journal article. This article presents a systematic literature review on the state of research concerning methodologies, applications and use cases of Twitter as a Location-Based Social Network.
The proposed systematic literature review method considers and combines search results from multiple heterogeneous digital libraries and allows an effective reproducible assessment of relevant research studies. Together with the implementation of an iterative keyword-based search considering metadata analysis results, it was possible to minimize bias during the overall review process. A combined approach of quantitative and qualitative review methods decreases the percentage of possible papers which have not been detected at all. One of the main advantages of the advanced systematic literature review, when compared with non-systematic reviews, is the degree of confidence that the available literature has been exhaustively and systematically searched. Non-systematic literature reviews are biased by the impact of human subjectivity, selecting relevant research papers in a non-reproducible, arbitrary manner. Papers identified in our systematic literature review have been selected from multiple electronic libraries and provide a much broader multidisciplinary perspective.
Finally, we were able to answer several research questions and provide new statistics-based insights for Twitter as a Location-Based Social Network. In this manner, we have shown the need for new research contributions from yet underrepresented disciplines within this systematic literature review and hope to further encourage and foster new research especially from the GIScience field. GIScience can contribute essential research methods in order to advance the research of Location-Based Social Networks by further integrating methods of spatial analysis. One GIScience research objective should be to develop novel methods and approaches towards the spatiotemporal analysis and exploration of social-media data by leveraging existing geographic knowledge. This research could provide stakeholders with near-real-time information and could lead to new insights by analyzing geographic and social aspects of Twitter.

Steiger, E. de Albuquerque, J. P. Zipf, A.(2015): An advanced systematic literature review on spatiotemporal analyses of Twitter data. Transactions in GIS.