It takes the average reader 3 hours and 5 minutes to read Information and Influence Propagation in Social Networks by Wei Chen
Assuming a reading speed of 250 words per minute. Learn more
Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models against any available real datasets consisting of a social network and propagation traces that occurred in the past? These are just some questions studied by researchers in this area. Information propagation models find applications in viral marketing, outbreak detection, finding key blog posts to read in order to catch important stories, finding leaders or trendsetters, information feed ranking, etc. A number of algorithmic problems arising in these applications have been abstracted and studied extensively by researchers under the garb of influence maximization. This book starts with a detailed description of well-established diffusion models, including the independent cascade model and the linear threshold model, that have been successful at explaining propagation phenomena. We describe their properties as well as numerous extensions to them, introducing aspects such as competition, budget, and time-criticality, among many others. We delve deep into the key problem of influence maximization, which selects key individuals to activate in order to influence a large fraction of a network. Influence maximization in classic diffusion models including both the independent cascade and the linear threshold models is computationally intractable, more precisely #P-hard, and we describe several approximation algorithms and scalable heuristics that have been proposed in the literature. Finally, we also deal with key issues that need to be tackled in order to turn this research into practice, such as learning the strength with which individuals in a network influence each other, as well as the practical aspects of this research including the availability of datasets and software tools for facilitating research. We conclude with a discussion of various research problems that remain open, both from a technical perspective and from the viewpoint of transferring the results of research into industry strength applications.
Information and Influence Propagation in Social Networks by Wei Chen is 179 pages long, and a total of 46,361 words.
This makes it 60% the length of the average book. It also has 57% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 4 hours and 13 minutes to read Information and Influence Propagation in Social Networks aloud.
Information and Influence Propagation in Social Networks is suitable for students ages 10 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
Information and Influence Propagation in Social Networks by Wei Chen is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.
To buy Information and Influence Propagation in Social Networks by Wei Chen on Amazon click the button below.
Buy Information and Influence Propagation in Social Networks on Amazon