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Social Network Analysis

Social Network Analysis
About the Course Everything is connected: people, information, events and places, all the more so with the advent of online social media. A practical way of making sense of the tangle of connections is to analyze them as networks. In this course you will learn about the structure and evolution of networks, drawing on knowledge from disciplines as diverse as sociology, mathematics, computer science, economics, and physics. Online interactive demonstrations and hands-on analysis of real-world data sets will focus on a range of tasks: from identifying important nodes in the network, to detecting communities, to tracing information diffusion and opinion formation. Course Syllabus Week 1: What are networks and what use is it to study them? Concepts: nodes, edges, adjacency matrix, one and two-mode networks, node degree Activity: Upload a social network (e.g. your Facebook social network into Gephi and visualize it ). Week 2: Random network models: Erdos-Renyi and Barabasi-Albert Week 4: Community

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GraphChi Disk-based large-scale graph computation Introduction GraphChi(huahua) is a spin-off of the GraphLab(rador) project. Create Something. Donate Login Remember Me Import Dynamic Data - Gephi:Wiki Introduction Longitudinal Networks Longitudinal (also named dynamic) networks are simply network that evolve in time.

Songwriting About the Course There’s a songwriter lurking somewhere inside you, peeking around corners, wondering if it’s safe to come out. Now it is. This course is an invitation to let your inner songwriter step into the sunlight. All it takes is a simple “yes” and you’ll be climbing that windy hill, marveling at the view. If you haven’t written any or many songs, this course will show you an efficient, effective process for tailoring songs to express your ideas and emotions.

Organizational Analysis About the Course Best MBA Mooc in 2013 as per review in the Financial Times! "The best [MBA Mooc] was Organizational Analysis taught by Stanford's Dan McFarland" - Philip D. Broughton MBA It is hard to imagine living in modern society without participating in or interacting with organizations. spheres spheres [ english | español | portugués ] Spherical Surface of Dialogue Spheres shaped by dialogue, a net of semantical combinations. Create a new strip You are using an ancient web browser, Stripgenerator does not work properly in it.Get rid of Internet Explorer 6! Upgrade to a new version or use another browser like Chrome, Opera, Safari or Firefox. StripGenerator

Gamification About the Course Gamification is the application of digital game design techniques to non-game contexts, such as business, education, and social impact challenges. Video games are the dominant entertainment form of modern times because they powerfully motivate behavior. Game mechanics can be applied outside the immersive environments of games themselves, to create engaging experiences as well as assign rewards and recognition.

Design: Creation of Artifacts in Society About the Course This is a course aimed at making you a better designer. The course marries theory and practice, as both are valuable in improving design performance. Lectures and readings will lay out the fundamental concepts that underpin design as a human activity. Weekly design challenges test your ability to apply those ideas to solve real problems. The course is deliberately broad - spanning all domains of design, including architecture, graphics, services, apparel, engineered goods, and products. Text Network Analysis Text network analysis allows one to quickly visualize the meanings and agendas present within a text, live conversation, broadcast, or interview. Our method is different to semantic network analysis. Instead, we focus predominantly on the relationships and clusters of meaning present within the text, uncovering what we call the pathways for meaning circulation Our interest lies in researching the topology of the resulting network, allowing us to focus on a text as a whole rather than its specific semantic parts. These topologies can then be compared with our extensive database in order to sort texts according to their structure rather than arbitrary categories they belong to. Text network analysis can also be used to build a map of sentiments and interests for any group.

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