Sunday, August 13, 2017

Predicting the Evolution of Narratives in Social Media


Building on our work on narratives and social media at the 15th International Symposium on Spatial and Temporal Databases (SSTD'17) we have a paper entitled: "Predicting the Evolution of Narratives in Social Media." In the paper we discuss briefly the challenges that social media poses with respect to understanding narratives and propose a framework that could be used to develop simulation models to predict the spread and evolution of narratives by blending the social, spatial and contextual dimensions of online narratives that are contextually informed by past events. Below you can read the abstract to our paper along with a link to the paper itself.
Abstract. The emergence of global networking capabilities (e.g. social media) has provided newfound mechanisms and avenues for information to be generated, disseminated, shaped, and consumed. The spread and evolution of online information represents a unique narrative ecosystem that is facilitated by cyberspace but operates at the nexus of three dimensions: the social network, the contextual, and the spatial. Current approaches to predict patterns of information spread across social media primarily focus on the social network dimension of the problem. The novel challenge formulated in this work is to blend the social, spatial, and contextual dimensions of online narratives in order to support high fidelity simulations that are contextually informed by past events, and support the multi-granular, reconfigural and dynamic prediction of the dissemination of a new narrative.



Full Reference:
Schmid, K. A. Zufle, A., Pfoser, D., Crooks, A.T., Croitoru, A. and Stefanidis, A. (2017), Predicting the Evolution of Narratives in Social Media, in Gertz, M., Renz, M., Zhou, X., Hoel, E., Ku, W.-S., Voisard, A., Zhang, C., Chen, H., Tang, L., Huang, Y., Lu, C.-T. and Ravada, S. (eds.) Advances in Spatial and Temporal Databases: Proceedings of the 2017 International Symposium on Spatial and Temporal Databases, Springer, New York, NY., pp. 388-392 (pdf)

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