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\cite{Coifman_2006} is a math theoretical article in wich it is shown that in the context of manifolds, graphs, data sets and general metric spaces, diffusion processes and Markov processes can be analyzed in  a multiscale fashion very much in the spirit of classical wavelet analysis. It is proposed fast and stable algorithms for constructing orthonormal bases for the multiscale approximation spaces, and it is shown that there is an efficient scaling function and wavelet transform.  \cite{Coifman_2011} harmonic ana analysis of databases  \cite{Sandryhaila_2013}  \subsection{Social Networks} 
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In \cite{Guille_2013} it is studied the information diffusion and prediction. The author surveys the research done, defines a new graph model: Time Based Asynchronous Independent Cascades (T-BaSIC) and provides an open source implementation SOcial Network DYnamics (SONDY). Definitions are provided for message topics, social influence, heard behaviour and informational cascade. A probability of information transmission between nodes is used in the model. Due to "closed world assumption" the model underestimates the volume.  \cite{Jain_2014}  \subsection{Spectral Information Retrieval}  \cite{Costa_2010} describes how the Discret Fourier Transform (DFT) can be used for Information Retrieval (IR). A query is represented as a sum of individual query terms represented as sinusoidal curves. The query function is transformed in the frequency domain through DFT resulting a spectrum. Each document is considered to be a set of filters that filter the query spectrum resulting a power that ranks the documents. The more the power of the spectrum is decreased the higher the document ranks. The model is named Least Spectral Power Ranking (LSPR). The model can be used for recommender systems.