ﻻ يوجد ملخص باللغة العربية
Due to popularity surge social networks became lucrative targets for spammers and guerilla marketers, who are trying to game ranking systems and broadcast their messages at little to none cost. Ranking systems, for example Twitters Trends, can be gamed by scripted users also called bots, who are automatically or semi-automatically twitting essentially the same message. Judging by the prices and abundance of supply from PR firms this is an easy to implement and widely used tactic, at least in Russian blogosphere. Aggregative analysis of social networks should at best mark those messages as spam or at least correctly downplay their importance as they represent opinions only of a few, if dedicated, users. Hence bot detection plays a crucial role in social network mining and analysis. In this paper we propose technique called RepRank which could be viewed as Markov chain based model for reputation propagation on graphs utilizing simultaneous trust and anti-trust propagation and provide effective numerical approach for its computation. Comparison with another models such as TrustRank and some of its modifications on sample of 320000 Russian speaking Twitter users is presented. The dataset is presented as well.
Twitter has become a major social media platform since its launching in 2006, while complaints about bot accounts have increased recently. Although extensive research efforts have been made, the state-of-the-art bot detection methods fall short of ge
Recommendation plays a key role in e-commerce and in the entertainment industry. We propose to consider successive recommendations to users under the form of graphs of recommendations. We give models for this representation. Motivated by the growing
Recently, in the context of covariance matrix estimation, in order to improve as well as to regularize the performance of the Tylers estimator [1] also called the Fixed-Point Estimator (FPE) [2], a shrinkage fixed-point estimator has been introduced
Processing of digital images is continuously gaining in volume and relevance, with concomitant demands on data storage, transmission and processing power. Encoding the image information in quantum-mechanical systems instead of classical ones and repl
Over the years, quantifying the similarity of nodes has been a hot topic in complex networks, yet little has been known about the distributions of node-similarity. In this paper, we consider a typical measure of node-similarity called the common neig