Identification of multi-scale signatures, which consists of identifying distinct signatures across a range of time scales, as opposed to sticking with a single one Studying multi-scale compositionality consists of identifying the compositional structures of social media dynamics, which generally covers two tasks:
While several recent works have investigated methods to identify patterns of social dynamics, in this paper, we study a new, unexplored perspective of social dynamics, namely, multi-scale compositionality. Consequently, understanding the structures behind social dynamics represents a central question in social networks research, with many important applications including political campaigning, viral marketing, and disaster response. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.Īll activities in social networks evolve over time. įunding: HP and RM are both funded by the United States National Science Foundation Grant CCF-1314876, Website. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedĭata Availability: The Twitter data is available from. Received: SeptemAccepted: JanuPublished: April 1, 2015Ĭopyright: © 2015 Peng, Marculescu. Citation: Peng H-K, Marculescu R (2015) Multi-Scale Compositionality: Identifying the Compositional Structures of Social Dynamics Using Deep Learning.
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