Motorola mt 777 uncover
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Previous work suggests that more research is needed to develop methods for exploiting the value of social media data while overcoming their limitations. However, many other studies have also pointed out the challenges that big data present and the likely methodological pitfalls that might result from their analysis ( 14– 19). A flurry of studies have analyzed the correlation of search engine queries, microblogging posts, and other open data sources with the incidence of infectious disease ( 1– 4), box office returns ( 5), stock market behavior ( 6, 7), election outcomes ( 8, 9), popular votes results ( 10), crowd sizes ( 11), and social unrest ( 12, 13). This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.Ī vivid scientific and popular media debate has recently centered on the role that social networking tools play in coordinating collective phenomena examples include street protests, civil unrests, consensus formation, and the emergence of electoral preferences. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena.
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MOTOROLA MT 777 UNCOVER SERIES
We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. Nonlinear Lorentz oscillators: Time scales, volume, and dynamical coupling.ĭata from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. Minimalist example: Disentangling volume and time scales (Δ t). Evolution of two nonlinear systems under four changing scenarios: from dynamic independence (β = 0) to strong asymmetric coupling (β = 20.0). Raw time series for Twitter unfiltered stream for Δ t = 600 s and Δ t = 45 s (left and right, respectively).įig. Thresholded T † matrices corresponding to different moments in the Twitter unfiltered data set.įig. Evolution of τ as a function of time.įig. Average total amount of STE for some Δ t (top panel) and time scale profile τ (bottom panel) for 15M data set constrained surrogates (20 randomizations).įig. Behavior of θ as a function of time for 15M and Outono Brasileiro data sets randomized surrogates.įig. Average total amount of STE for some Δ t (top panel) and time scale profile τ (bottom panel) for 15M data set amplitude adjusted Fourier transform surrogates (50 randomizations).įig. Behavior of θ as a function of time for four data sets at alternative geographical aggregation levels.įig. Normalized directionality index for four data sets at alternative geographical aggregation levels.įig. Characteristic time scale τ for four data sets at alternative geographical aggregation levels.įig. Normalized directionality index for each geographical unit in the 15M data set for different m.įig. Fraction of false nearest neighbors as a function of m for the Spanish data set and the Madrid time series.įig. Normalized directionality index for each geographical unit in the 15M data set for different ω.įig. Dependence of τ with the sliding window size ω, considering the Spanish 15M protest.įig. Evolution of the order parameter θ for thresholded (green) and raw (red) T † matrices.įig. Schematic view of the sliding window scheme.įig.
MOTOROLA MT 777 UNCOVER MOVIE
Schematic representation of the algorithm used to gather geographical coordinates of the Hollywood movie release and the Google-Motorola acquisition data sets.įig. List of keywords used to find tweets related to the Outono Brasileiro.įig. Validation of results (III): Synthetic time series generation
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Validation of results (II): Unfiltered Twitter stream Validation of results (I): Time series randomization Sensibility analysis of the parametrization Supplementary material for this article is available at ĭata, context, and chronology of the events analyzed