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A conceptual framework for studying collective reactions to events in location-based social media

Dunkel, A., Andrienko, G. ORCID: 0000-0002-8574-6295, Andrienko, N. ORCID: 0000-0003-3313-1560 , Burghardt, D., Hauthal, E. & Purves, R. (2018). A conceptual framework for studying collective reactions to events in location-based social media. International Journal of Geographical Information Science, doi: 10.1080/13658816.2018.1546390


Events are a core concept of spatial information, but location-based social media (LBSM) provide information on reactions to events. Individuals have varied degrees of agency in initiating, reacting to or modifying the course of events, and reactions include observations of occurrence, expressions containing sentiment or emotions, or a call to action. Key characteristics of reactions include referent events and information about who reacted, when, where and how. Collective reactions are composed of multiple individual reactions sharing common referents. They can be characterized according to the following dimensions: spatial, temporal, social, thematic and interlinkage. We present a conceptual framework, which allows characterization and comparison of collective reactions. For a thematically well-defined class of event such as storms, we can explore differences and similarities in collective attribution of meaning across space and time. Other events may have very complex spatio-temporal signatures (e.g. political processes such as Brexit or elections), which can be decomposed into series of individual events (e.g. a temporal window around the result of a vote). The purpose of our framework is to explore ways in which collective reactions to events in LBSM can be described and underpin the development of methods for analysing and understanding collective reactions to events.

Publication Type: Article
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Geographical Information Science on 18 Nov 2018, available online:
Publisher Keywords: Spatio-temporal, social, event-reaction, information-spread, sentiment
Subjects: H Social Sciences > HM Sociology
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: City, University of London (2022-) > School of Science & Technology > Computer Science
School of Mathematics, Computer Science & Engineering > Computer Science > giCentre
Text - Accepted Version
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