Modeling Adoption and Usage of Competing Products

The emergence and wide-spread use of online social networks has led to a dramatic increase on the availability of social activity data. Importantly, this data can be exploited to investigate, at a microscopic level, some of the problems that have captured the attention of economists, marketers and sociologists for decades, such as, e.g., product adoption, usage and competition. In this paper, we propose a continuous-time probabilistic model, based on temporal point processes, for the adoption and frequency of use of competing products, where the frequency of use of one product can be modulated by those of others. This model allows us to efficiently simulate the adoption and recurrent usages of competing products, and generate traces in which we can easily recognize the effect of social influence, recency and competition. We then develop an inference method to efficiently fit the model parameters by solving a convex program. The problem decouples into a collection of smaller subproblems, thus scaling easily to networks with hundred of thousands of nodes. We validate our model over synthetic and real diffusion data gathered from Twitter, and show that the proposed model does not only provides a good fit to the data and more accurate predictions than alternatives but also provides interpretable model parameters, which allow us to gain insights into some of the factors driving product adoption and frequency of use

Productivity and Environmental Performance in Marketing Cooperatives: Incentive Schemes on the Horticultural Sector

The object of the present paper is to analyze the productivity of marketing cooperatives incorporating environmental inputs/outputs. In the European agricultural policy, expectations for attaining sustainable and competitive agriculture lie to a great extent on the cooperative sector's ability to adapt to the new market conditions. These challenges have led marketing cooperatives in the fruit and vegetables sector to consider improvement in productivity and sound environmental performance. In this sector environmental management was intensified by the Common Agrarian Policy (CAP) through incentives on the so-called Operative Programs (OP). The present study analyses the total factor productivity (TFP) related to environmental variables in this sector using a parametric-stochastic approach and taking as reference a panel data of Spanish cooperatives for the period 1994-2002. Additionally, the determinants of productivity environmental indices are examined econ ometrically. The estimates obtained show a relevant increase in the efficiency component for the period under study and a relatively low impact of incentive schemes. However, they also show a relationship between productivity changes and several management factors in cooperatives, such as labor quality, capital intensity and environmental spillover.Productivity, environmental performance, parametric approach, efficiency, marketing cooperative, horticultural sector, Agribusiness, Environmental Economics and Policy, Productivity Analysis, D24, Q13, Q21, L15,

Uncovering the Temporal Dynamics of Diffusion Networks

Time plays an essential role in the diffusion of information, influence and disease over networks. In many cases we only observe when a node copies information, makes a decision or becomes infected -- but the connectivity, transmission rates between nodes and transmission sources are unknown. Inferring the underlying dynamics is of outstanding interest since it enables forecasting, influencing and retarding infections, broadly construed. To this end, we model diffusion processes as discrete networks of continuous temporal processes occurring at different rates. Given cascade data -- observed infection times of nodes -- we infer the edges of the global diffusion network and estimate the transmission rates of each edge that best explain the observed data. The optimization problem is convex. The model naturally (without heuristics) imposes sparse solutions and requires no parameter tuning. The problem decouples into a collection of independent smaller problems, thus scaling easily to networks on the order of hundreds of thousands of nodes. Experiments on real and synthetic data show that our algorithm both recovers the edges of diffusion networks and accurately estimates their transmission rates from cascade data.Comment: To appear in the 28th International Conference on Machine Learning (ICML), 2011. Website: http://www.stanford.edu/~manuelgr/netrate

Diversidad de la comunidad liquénica en un bosque remanente del sur de la región chaqueña (Córdoba, Argentina)

The lichen community diversity in patches of Chaco forest -NE of Cordoba Province, Argentina- was analyzed. Fifteen forest patches embedded in farmland areas were sampled. Size of the patch and exposure to the crops, were registered. In each patch, ten trees (sample units) with epiphytic lichens were sampled. The cover for epiphytic lichen species and the number of species present were recorded. Shannon-Wiener diversity index was calculated for each patches and Multivariate Analysis (DCA and Indicator Species Analysis) were applied in order to study the composition of the community. The sample patches in the DCA were associated with patch exposition. Four quantitative variables (patch size, relative cover of Physciaceae, Parmeliaceae and Collemataceae families that was the most representative) were related with the first two axes of DCA using correlations coefficients. Twenty one species in patches were identified. The diversity ?richness and cover- have not relation with the patches characteristics. Multivariate Analysis of sample units showed preferences of some species to exposure of patches to the crops. The data indicated that there would be a degradation marked by the impact of the edges on the remaining forests. There is a trend towards more homogeneous communities, formed by species resistant to these boundary conditions and with high coverage.Se analizó la diversidad de la comunidad liquénica del bosque chaqueño en el NE de la provincia de Córdoba, Argentina. Se registraron quince parches de bosque inmersos en áreas de cultivo, su exposición a los cultivos y el tamaño de los parches. En cada parche se muestrearon los líquenes epífitos de diez árboles (unidades muestrales). Se registró la cobertura y el número de especies presentes. Se calculó el índice de diversidad de Shannon-Wiener para cada parche y se aplicaron análisis multivariados (análisis de correspondencia detendenciado -DCA- e índice de indicador de especies) para estudiar la composición de la comunidad. En el DCA se asoció la muestra de parche con su exposición. Se relacionaron cuatro variables cuantitativas (tamaño del parche, cobertura relativa de familias, Physciaceae, Parmeliaceae y Collemataceae, que fueron las más representativas) con los primeros dos ejes del DCA, usando coeficiente de correlación. Se identificaron 21 especies en los parches. El análisis multivariado de las unidades muestrales evidenció preferencia de algunas especies a la exposición de los parches al cultivo. Los datos muestran una degradación debida al impacto del borde en el bosque remanente. Existe una tendencia hacia las comunidades más homogéneas, formadas por especies resistentes a estas condiciones de borde y que presentan altos valores de cobertura.Fil: Estrabou, Cecilia. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Ecología y Recursos Naturales Renovables; ArgentinaFil: Quiroga, Carolina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Ecología y Recursos Naturales Renovables; ArgentinaFil: Rodriguez, Juan Manuel. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Ecología y Recursos Naturales Renovables; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentin

Young stellar objects from soft to hard X-rays

Magnetically active stars are the sites of efficient particle acceleration and plasma heating, processes that have been studied in detail in the solar corona. Investigation of such processes in young stellar objects is much more challenging due to various absorption processes. There is, however, evidence for violent magnetic energy release in very young stellar objects. The impact on young stellar environments (e.g., circumstellar disk heating and ionization, operation of chemical networks, photoevaporation) may be substantial. Hard X-ray devices like those carried on Simbol-X will establish a basis for detailed studies of these processes.Comment: Proc. "Simbol-X: Focusing on the Hard X-Ray Universe", Paris, 2-5 Dec. 2008, ed. J. Rodriguez and P. Ferrando, in press; 6 pages, 4 figure

Structure and Dynamics of Information Pathways in Online Media

Diffusion of information, spread of rumors and infectious diseases are all instances of stochastic processes that occur over the edges of an underlying network. Many times networks over which contagions spread are unobserved, and such networks are often dynamic and change over time. In this paper, we investigate the problem of inferring dynamic networks based on information diffusion data. We assume there is an unobserved dynamic network that changes over time, while we observe the results of a dynamic process spreading over the edges of the network. The task then is to infer the edges and the dynamics of the underlying network. We develop an on-line algorithm that relies on stochastic convex optimization to efficiently solve the dynamic network inference problem. We apply our algorithm to information diffusion among 3.3 million mainstream media and blog sites and experiment with more than 179 million different pieces of information spreading over the network in a one year period. We study the evolution of information pathways in the online media space and find interesting insights. Information pathways for general recurrent topics are more stable across time than for on-going news events. Clusters of news media sites and blogs often emerge and vanish in matter of days for on-going news events. Major social movements and events involving civil population, such as the Libyan's civil war or Syria's uprise, lead to an increased amount of information pathways among blogs as well as in the overall increase in the network centrality of blogs and social media sites.Comment: To Appear at the 6th International Conference on Web Search and Data Mining (WSDM '13