Ask the Scientist project

Resources for the project

Power and Influence

Like any form of human interaction and communication it is possible to view Social Media as a means for the powerful to influence and control the less powerful. But what is power on social media, how might we measure or affect it, and does it translate to the real world? In this lecture we will look at the philosophical definitions of power, and explore how it has been analysed in social networks and social media systems. We will also look at the characteristics of social networks that impact on power, including Homophily, Heterophily, CyberBalkanization and Thresholds of Collective Action. Finally we will ask what evidence there is that power in social media can affect what goes on in the real world, and explore some real and fictional examples of protest to see what the consequences of social media actually are on sometimes violent political debate.

The Web 2.0 Development Survival Guide

Building software for Web 2.0 and the Social Media world is non-trivial. It requires understanding how to create infrastructure that will survive at Web scale, meaning that it may have to deal with tens of millions of individual items of data, and cope with hits from hundreds of thousands of users every minute. It also requires you to build tools that will be part of a much larger ecosystem of software and application families. In this lecture we will look at how traditional relational database systems have tried to cope with the scale of Web 2.0, and explore the NoSQL movement that seeks to simplify data-storage and create ultra-swift data systems at the expense of immediate consistency. We will also look at the range of APIs, libraries and interoperability standards that are trying to make sense of the Social Media world, and ask what trends we might be seeing emerge.

Technology Enhanced Learning Guide

Technology is changing how students learn and how we research. Perhaps you want to use technology to enhance communication or improve student support. You may want create a distance learning activity, a flexibly delivered module or indeed a whole course. You may simply want to find out where to find authoritative information, or to see what support exists for this type of work. The University is committed to delivering high quality learning and teaching, using technology where appropriate, in order to offer a distinctive Southampton educational experience. Technology Enhanced Learning (TEL), also known as e‑learning, is becoming increasingly important to students, teaching staff and the institution. This guide highlights some of the most important matters to consider. It is intended to help you to tackle the key issues that determine the success of TEL projects and to work on those projects in a considered way. Written with the input of colleagues from around the University, it prompts you to ask important questions and points you to sources of up-to-date knowledge and advice. Technology changes rapidly. This guide is about managing the work in a practical way. The University supports the use of a variety of TEL approaches for teaching and learning and colleagues are ready to offer their experience and advice. Each person has distinctive skills and specific experiences. No single person will have all the answers you are looking for. Be ready to investigate alternative approaches that suit you and your students’ needs in different ways. - Madeline Paterson, University of Southampton

COMP6037 Seminar 23 10 13: Science, knowledge and technology

Set readings 1. Sismondo S. (2009). The Kuhnian revolution. In An introduction to science and technology studies. p12-22 2. Ben-David J, Sullivan T. (1975) Sociology of science. Annual Review of Sociology p203-21 3. Clarke A, Star SL. (2008) The social worlds framework: a theory/methods package. In Hackett EJ et al. The handbook of science and technology studies. Cambridge MA: MIT Press p113-137 Bonus paper (read if you have time) 4. Mitroff I. (1974). Norms and Counternorms in a Select Group of Apollo Moon Scientists. American Sociological Review 39:79-95 • Aim to ensure that you understand the core arguments of each paper • Look up/note any new terminology (and questions you want to ask) • Think about your critical appraisal of the paper (what are the merits/demerits of the argument, evidence etc) In the seminar we will spend about 5 minutes talking about each paper, and then - building on the two lectures - discuss how these ideas might be used to think about the Web and Web Science. At the end there will be some time for questions and a chance to note your key learning points.

Big Data or Right Data?

Abstract Big data nowadays is a fashionable topic, independently of what people mean when they use this term. But being big is just a matter of volume, although there is no clear agreement in the size threshold. On the other hand, it is easy to capture large amounts of data using a brute force approach. So the real goal should not be big data but to ask ourselves, for a given problem, what is the right data and how much of it is needed. For some problems this would imply big data, but for the majority of the problems much less data will and is needed. In this talk we explore the trade-offs involved and the main problems that come with big data using the Web as case study: scalability, redundancy, bias, noise, spam, and privacy. Speaker Biography Ricardo Baeza-Yates Ricardo Baeza-Yates is VP of Research for Yahoo Labs leading teams in United States, Europe and Latin America since 2006 and based in Sunnyvale, California, since August 2014. During this time he has lead the labs in Barcelona and Santiago de Chile. Between 2008 and 2012 he also oversaw the Haifa lab. He is also part time Professor at the Dept. of Information and Communication Technologies of the Universitat Pompeu Fabra, in Barcelona, Spain. During 2005 he was an ICREA research professor at the same university. Until 2004 he was Professor and before founder and Director of the Center for Web Research at the Dept. of Computing Science of the University of Chile (in leave of absence until today). He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989. Before he obtained two masters (M.Sc. CS & M.Eng. EE) and the electronics engineer degree from the University of Chile in Santiago. He is co-author of the best-seller Modern Information Retrieval textbook, published in 1999 by Addison-Wesley with a second enlarged edition in 2011, that won the ASIST 2012 Book of the Year award. He is also co-author of the 2nd edition of the Handbook of Algorithms and Data Structures, Addison-Wesley, 1991; and co-editor of Information Retrieval: Algorithms and Data Structures, Prentice-Hall, 1992, among more than 500 other publications. From 2002 to 2004 he was elected to the board of governors of the IEEE Computer Society and in 2012 he was elected for the ACM Council. He has received the Organization of American States award for young researchers in exact sciences (1993), the Graham Medal for innovation in computing given by the University of Waterloo to distinguished ex-alumni (2007), the CLEI Latin American distinction for contributions to CS in the region (2009), and the National Award of the Chilean Association of Engineers (2010), among other distinctions. In 2003 he was the first computer scientist to be elected to the Chilean Academy of Sciences and since 2010 is a founding member of the Chilean Academy of Engineering. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow.