相关论文: Predicting Successful Memes using Network and Comm…

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily.…

Can we predict the future popularity of a song, movie or tweet? Recent work suggests that although it may be hard to predict an item's popularity when it is first introduced, peeking into its early adopters and properties of their social…

Detecting and characterizing emerging topics of discussion and consumer trends through analysis of Internet data is of great interest to businesses. This paper considers the problem of monitoring the Web to spot emerging memes - distinctive…

The proliferation of online communities has created exciting opportunities to study the mechanisms that explain group success. While a growing body of research investigates community success through a single measure -- typically, the number…

Predicting the popularity of content is important for both the host and users of social media sites. The challenge of this problem comes from the inequality of the popularity of con- tent. Existing methods for popularity prediction are…

Social media expose millions of users every day to information campaigns --- some emerging organically from grassroots activity, others sustained by advertising or other coordinated efforts. These campaigns contribute to the shaping of…

Predicting the future direction of community evolution is a problem with high theoretical and practical significance. It allows to determine which characteristics describing communities have importance from the point of view of their future…

Online social media have greatly affected the way in which we communicate with each other. However, little is known about what are the fundamental mechanisms driving dynamical information flow in online social systems. Here, we introduce 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…

The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different…

Predicting risk profiles of individuals in networks (e.g.~susceptibility to a particular disease, or likelihood of smoking) is challenging for a variety of reasons. For one, `local' features (such as an individual's demographic information)…

Internet memes have become an increasingly pervasive form of contemporary social communication that attracted a lot of research interest recently. In this paper, we analyze the data of 129,326 memes collected from Reddit in the middle of…

Predicting when an individual will adopt a new behavior is an important problem in application domains such as marketing and public health. This paper examines the perfor- mance of a wide variety of social network based measurements…

News articles are extremely time sensitive by nature. There is also intense competition among news items to propagate as widely as possible. Hence, the task of predicting the popularity of news items on the social web is both interesting…

As a fundamental structure in real-world networks, in addition to graph topology, communities can also be reflected by abundant node attributes. In attributed community detection, probabilistic generative models (PGMs) have become the…

Forecasting the popularity of new songs has become a standard practice in the music industry and provides a comparative advantage for those that do it well. Considerable efforts were put into machine learning prediction models for that…

Topic popularity prediction in social networks has drawn much attention recently. Various elegant models have been proposed for this issue. However, different datasets and evaluation metrics they use lead to low comparability. So far there…

The diffusion of information and behaviors over social networks is of considerable interest in research fields ranging from sociology to computer science and application domains such as marketing, finance, human health, and national…

Groups - social communities are important components of entire societies, analysed by means of the social network concept. Their immanent feature is continuous evolution over time. If we know how groups in the social network has evolved we…

The importance of the ability of predict trends in social media has been growing rapidly in the past few years with the growing dominance of social media in our everyday's life. Whereas many works focus on the detection of anomalies in…