相关论文: A Bayesian approach for predicting the popularity …

Bayesian Persuasion is proposed as a tool for social media platforms to combat the spread of misinformation. Since platforms can use machine learning to predict the popularity and misinformation features of to-be-shared posts, and users are…

Social networks readily transmit information, albeit with less than perfect fidelity. We present a large-scale measurement of this imperfect information copying mechanism by examining the dissemination and evolution of thousands of memes,…

Social networks play a fundamental role in propagation of information and news. Characterizing the content of the messages becomes vital for different tasks, like breaking news detection, personalized message recommendation, fake users…

Most studies on social influence have focused on direct influence, while another interesting question can be raised as whether indirect influence exists between two users who're not directly connected in the network and what affects such…

Arguably one of the most important features of Twitter is the support for "retweets" or messages re-posted verbatim by a user that were originated by someone else. (This does not include modified tweets that sometimes are referred to as…

We present a new inference method based on approximate Bayesian computation for estimating parameters governing an entire network based on link-traced samples of that network. To do this, we first take summary statistics from an observed…

A model for the spreading of online information or "memes" on multiplex networks is introduced and analyzed using branching-process methods. The model generalizes that of [Gleeson et al., Phys.Rev. X., 2016] in two ways. First, even for a…

Predicting the future popularity of online content is highly important in many applications. Preferential attachment phenomena is encountered in scale free networks.Under it's influece popular items get more popular thereby resulting in…

Online hate speech, particularly over microblogging platforms like Twitter, has emerged as arguably the most severe issue of the past decade. Several countries have reported a steep rise in hate crimes infuriated by malicious hate…

How predictable is success in complex social systems? In spite of a recent profusion of prediction studies that exploit online social and information network data, this question remains unanswered, in part because it has not been adequately…

We propose an end-to-end neural network to predict the geolocation of a tweet. The network takes as input a number of raw Twitter metadata such as the tweet message and associated user account information. Our model is language independent,…

The link between affect, defined as the capacity for sentimental arousal on the part of a message, and virality, defined as the probability that it be sent along, is of significant theoretical and practical importance, e.g. for viral…

Twitter has been a focus of research in political science for a few years now as it provides the opportunity to make direct observations on the spread of political information in different communities. Here we will be studying the phenomena…

Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. In this paper we adapt existing bio-surveillance algorithms to…

Increasing evidence suggests that a growing amount of social media content is generated by autonomous entities known as social bots. In this work we present a framework to detect such entities on Twitter. We leverage more than a thousand…

Predicting the popularity of online content has attracted much attention in the past few years. In news rooms, for instance, journalists and editors are keen to know, as soon as possible, the articles that will bring the most traffic into…

Today, our more-than-ever digital lives leave significant footprints in cyberspace. Large scale collections of these socially generated footprints, often known as big data, could help us to re-investigate different aspects of our social…

Predicting X from Twitter is a popular fad within the Twitter research subculture. It seems both appealing and relatively easy. Among such kind of studies, electoral prediction is maybe the most attractive, and at this moment there is a…

Many modern data analysis problems involve inferences from streaming data. However, streaming data is not easily amenable to the standard probabilistic modeling approaches, which assume that we condition on finite data. We develop…

The dynamics of popularity in online media are driven by a combination of endogenous spreading mechanisms and response to exogenous shocks including news and events. However, little is known about the dependence of temporal patterns of…