We consider the problem of active coarse ranking, where the goal is to sort items according to their means into clusters of prespecified sizes, by adaptively sampling from their reward distributions. This setting is useful in many social science applications involving human raters and the approximate rank of every item is desired. Approximate or coarse ranking can significantly reduce the numbe...

Real-world networks exhibit significant community structure. Communities are sometimes explicitly known or defined (e.g., virtual groups that one joins in an online social network, departments in an organization), but are often determined using a community detection or a clustering algorithm. Given a weighted network, with edge weights denoting interaction strengths between vertices, and a mapp...

In this paper, we present algorithms for ranking nodes in interaction networks. Informally, they capture the patterns of historical interaction among the nodes and the associated outcomes. There exists a cardinal ranking over the set of outcomes, characterizing the order of preference. We argue that ranking of nodes should be influenced by both structural properties of the networks and the outc...

Networks have attracted a great deal of attention the last decade, and play an important role in various scientific disciplines. Ranking nodes in such networks, based on for example PageRank or eigenvector centrality, remains a hot topic. Not only does this have applications in ranking web pages, it also allows peer-to-peer systems to have effective notions of trust and reputation and enables a...

Online fake news can generate a negative impact on both users and society. Due to the concerns with spread of misinformation, assessing network influence online has become an important issue. This study quantifies nodes by proposing algorithm based information entropy theory. Dynamic process is characterized mobile social networks (MSNs). Weibo (i.e., Chinese version microblogging) are chosen b...

Ranking tweets is a fundamental task to make it easier to distill the vast amounts of information shared by users. In this paper, we explore the novel idea of ranking tweets on a topic using heterogeneous networks. We construct heterogeneous networks by harnessing cross-genre linkages between tweets and semantically-related web documents from formal genres, and inferring implicit links between ...

Nowadays, several crowdsourcing projects exploit social choice methods for computing an aggregate ranking of alternatives given individual rankings provided by workers. Motivated by such systems, we consider a setting where each worker is asked to rank a fixed (small) number of alternatives and, then, a positional scoring rule is used to compute the aggregate ranking. Among the apparently infin...

This paper presents the RECOD team experience in the Retrieving Diverse Social Images Task at MediaEval 2016. The teams were required to develop a diversification approach for social photo retrieval. Our proposal is based on re-ranking, rank aggregation, and diversity promotion, allowing employment of textual and visual information apart or fused.