Robust PCA for Anomaly Detection and Data Imputation in Seasonal Time Series

We propose a robust principal component analysis (RPCA) framework to recover low-rank and sparse matrices from temporal observations. We develop an online version of the batch temporal algorithm in order to process larger datasets or streaming data. We empirically compare the proposed approaches with different RPCA frameworks and show their effectiveness in practical situations

Link weights recovery in heterogeneous information networks

International audienceSocio-technical systems usually consist of many intertwined networks, each connecting different types of objects or actors through a variety of means. As these networks are co-dependent, one can take advantage of this entangled structure to study interaction patterns in a particular network from the information provided by other related networks. A method is, hence, proposed and tested to recover the weights of missing or unobserved links in heterogeneous information networks (HIN)—abstract representations of systems composed of multiple types of entities and their relations. Given a pair of nodes in a HIN, this work aims at recovering the exact weight of the incident link to these two nodes, knowing some other links present in the HIN. To do so, probability distributions resulting from path-constrained random walks, i.e., random walks where the walker is forced to follow only a specific sequence of node types and edge types, capable to capture specific semantics and commonly called a meta-path, are combined in a linearly fashion to approximate the desired result. This method is general enough to compute the link weight between any types of nodes. Experiments on Twitter and bibliographic data show the applicability of the method

The International Geomedia Agenda: ODYCCEUS Deliverable 1.3

This deliverable provides conceptual grounds for the analysis of opinions about international conflicts in the media, crossing the perspectives of quantitative geography and media studies. In particular, it presents the state of the art of interdisciplinary literature about the agenda setting and the role of information gatekeepers; it provides a theoretical typology of literature about public opinion analysis in social media; it studies connections in agent-based social models between mass media and social media in setting the agenda and influencing opinions; and finally it investigates how these topics have been developed in the literature related to international conflicts

The International Geomedia Agenda: ODYCCEUS Deliverable 1.3

This deliverable provides conceptual grounds for the analysis of opinions about international conflicts in the media, crossing the perspectives of quantitative geography and media studies. In particular, it presents the state of the art of interdisciplinary literature about the agenda setting and the role of information gatekeepers; it provides a theoretical typology of literature about public opinion analysis in social media; it studies connections in agent-based social models between mass media and social media in setting the agenda and influencing opinions; and finally it investigates how these topics have been developed in the literature related to international conflicts

The International Geomedia Agenda: ODYCCEUS Deliverable 1.3

This deliverable provides conceptual grounds for the analysis of opinions about international conflicts in the media, crossing the perspectives of quantitative geography and media studies. In particular, it presents the state of the art of interdisciplinary literature about the agenda setting and the role of information gatekeepers; it provides a theoretical typology of literature about public opinion analysis in social media; it studies connections in agent-based social models between mass media and social media in setting the agenda and influencing opinions; and finally it investigates how these topics have been developed in the literature related to international conflicts