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Number of items: 70.

"Thematically Analysing Social Network Content During Disasters Through the Lens of the Disaster Management Lifecycle" & "Investigating Similarity Between Privacy Policies of Social Networking Sites as a Precursor for Standardization"
Abstract 1: Social Networks such as Twitter are often used for disseminating and collecting information during natural disasters. The potential for its use in Disaster Management has been acknowledged. However, more nuanced understanding of the communications that take place on social networks are required to more effectively integrate this information into the processes within disaster management. The type and value of information shared should be assessed, determining the benefits and issues, with credibility and reliability as known concerns. Mapping the tweets in relation to the modelled stages of a disaster can be a useful evaluation for determining the benefits/drawbacks of using data from social networks, such as Twitter, in disaster management.A thematic analysis of tweets’ content, language and tone during the UK Storms and Floods 2013/14 was conducted. Manual scripting was used to determine the official sequence of events, and classify the stages of the disaster into the phases of the Disaster Management Lifecycle, to produce a timeline. Twenty- five topics discussed on Twitter emerged, and three key types of tweets, based on the language and tone, were identified. The timeline represents the events of the disaster, according to the Met Office reports, classed into B. Faulkner’s Disaster Management Lifecycle framework. Context is provided when observing the analysed tweets against the timeline. This illustrates a potential basis and benefit for mapping tweets into the Disaster Management Lifecycle phases. Comparing the number of tweets submitted in each month with the timeline, suggests users tweet more as an event heightens and persists. Furthermore, users generally express greater emotion and urgency in their tweets.This paper concludes that the thematic analysis of content on social networks, such as Twitter, can be useful in gaining additional perspectives for disaster management. It demonstrates that mapping tweets into the phases of a Disaster Management Lifecycle model can have benefits in the recovery phase, not just in the response phase, to potentially improve future policies and activities. Abstract2: The current execution of privacy policies, as a mode of communicating information to users, is unsatisfactory. Social networking sites (SNS) exemplify this issue, attracting growing concerns regarding their use of personal data and its effect on user privacy. This demonstrates the need for more informative policies. However, SNS lack the incentives required to improve policies, which is exacerbated by the difficulties of creating a policy that is both concise and compliant. Standardization addresses many of these issues, providing benefits for users and SNS, although it is only possible if policies share attributes which can be standardized. This investigation used thematic analysis and cross- document structure theory, to assess the similarity of attributes between the privacy policies (as available in August 2014), of the six most frequently visited SNS globally. Using the Jaccard similarity coefficient, two types of attribute were measured; the clauses used by SNS and the coverage of forty recommendations made by the UK Information Commissioner’s Office. Analysis showed that whilst similarity in the clauses used was low, similarity in the recommendations covered was high, indicating that SNS use different clauses, but to convey similar information. The analysis also showed that low similarity in the clauses was largely due to differences in semantics, elaboration and functionality between SNS. Therefore, this paper proposes that the policies of SNS already share attributes, indicating the feasibility of standardization and five recommendations are made to begin facilitating this, based on the findings of the investigation.

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A data-driven approach to disease control
As our world becomes increasingly interconnected, diseases can spread at a faster and faster rate. Recent years have seen large-scale influenza, cholera and ebola outbreaks and failing to react in a timely manner to outbreaks leads to a larger spread and longer persistence of the outbreak. Furthermore, diseases like malaria, polio and dengue fever have been eliminated in some parts of the world but continue to put a substantial burden on countries in which these diseases are still endemic. To reduce the disease burden and eventually move towards countrywide elimination of diseases such as malaria, understanding human mobility is crucial for both planning interventions as well as estimation of the prevalence of the disease. In this talk, I will discuss how various data sources can be used to estimate human movements, population distributions and disease prevalence as well as the relevance of this information for intervention planning. Particularly anonymised mobile phone data has been shown to be a valuable source of information for countries with unreliable population density and migration data and I will present several studies where mobile phone data has been used to derive these measures.

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An Economists View of Web Science
Social Networking explained by an economic model of cost and benefit.

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Art & the Web
A introduction to how artists and designers and using the web and adapting to the web

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COMP3016 Web Technology - Strand "Web Science" Lecture 1
Lecture 1: Introduction to Web Science Lecture slides and video by Directors of Web Science Research Initiative (Wendy Hall and Tim Berners-Lee)

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COMP3016 Web Technology - Strand "Web Science" Lecture 2
Lecture 2: Personal Privacy and State Interference Lecture slides and video by Danny Weitzner.

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COMP3016 Web Technology - Strand 3 "History" Lecture 1
Lecture 1: The Pioneers and History of Hypertext (pre-WWW) Contains Powerpoint Lecture slides and Hypertext Research Papers: Bush: As We may Think; Engelbart: NLS and A Framework for Augmenting Human Intelligence; Nelson: Xanalogical Structure; Conklin: A Survey of Hypertext; Halasz 1987: Reflections on NoteCards: Seven Issues for the Next Generation of Hypermedia Systems; Berners-Lee 1994 The World-Wide Web.

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COMP3016 Web Technology - Strand 3 "History" Lecture 2
Lecture 1: Contributions of Pre WWW Research: Open Hypermedia Systems Contains Powerpoint Lecture slides and Hypertext Research Papers: Industrial Strength Hypermedia: Requirements for a Large Engineering Enterprise (Malcolm et al. 1991); Towards An Integrated Information Environment With Open Hypermedia Systems (Davis et al. 1992); Unifying Strategies for Web Augmentation (Bouvin 1999); Hyper-G (Adapted from Lowe and Hall); OHP:A Draft Proposal for a Standard Open Hypermedia Protocol (Davis et al. 1996); XML Linking (DeRose 99)

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COMP3016 Web Technology - Strand 3 "History" Lecture 3
Lecture 3: Contributions of Pre WWW Research: Spatial Hypertext and Temporal Hypertext Contains Powerpoint Lecture slides and Hypertext Research Papers: Spatial [SPATIAL] VIKI: spatial hypertext supporting emergent structure (Marshall, 94); Towards Geo-Spatial Hypermedia: Concepts and Prototype Implementation, (Gronbaek et al. 2002); Cyber Geography and Better Search Engines; [TEMPORAL] Anticipating SMIL 2.0: The Developing Cooperative Infrastructure for Multimedia on the Web (Rutledge 1999); Its About Time: Link Streams as Continuous Metadata (Page et al., 2001); Everything You Wanted to Know About MPEG-7:Part 1 (Nack & Lindsay 1999)

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COMP3016 Web Technology - Strand 3 "History" Lecture 4
Lecture 4: Ontological Hypertext and the Semantic Web Contains Powerpoint Lecture slides and Hypertext Research Papers: Conceptual linking: Ontology-based Open Hypermedia (Carr et al. 2001); CS AKTiveSpace: Building a Semantic Web Application (Glaser et al., 2004); The Semantic Web Revisited (Shadbolt, Hall and Berners-Lee, 2006); Mind the Semantic Gap (Millard et al., 2005).

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COMP3016 Web Technology - Strand 3 "History" Lecture 5
Lecture 5: Web 2.0 and Social Hypertext Contains Powerpoint Lecture slides and Hypertext Research Papers: What Is Web 2.0 Design Patterns and Business Models for the Next Generation of Software . Tim O'Reilly (2005); Web 2.0: Hypertext by Any Other Name? (Millard & Ross, 2006)

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COMP3016 Web Technology - Strand 3 "History" Lecture 6
Lecture 6: Where are all the links taking us: Web Science Contains Powerpoint Lecture slides and Hypertext Research Papers: The Literati (The Cyberspace and critical theory website) (Eastgate website); Pervasive Hypertext at Southampton and at Aarhus; Adaptive Hypertext - The Next Big Thing: (De Bra & Chepegin, 2004); Web Science: Creating a Science of the Web (Berners-Lee, Hall, Hendler, Shadbolt & Weitzner, 2006).

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And 6 more...
COMP6037 - Readings
Attached are the readings from past and present COMP6037 lectures.

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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.

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Communities and the Web
What is a social network? How does an online community differ from a real world community? See also: Anne Hornsby, 'Surfing the net for community: a Durkheimian analysis of electronic gatherings' ch.3 in Peter Kivisto (ed.) Illuminating Social Life (3rd ed 2005). Libr ref HM51KIV. Graham Crow and Catherine Maclean, 'Community' in Geoff Payne (ed.) Social Divisions (2nd ed. 2006) HM821PAY.

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Dynamic Document Generation from Semantic Web Data
This talk will present an overview of the ongoing ERCIM project SMARTDOCS (SeMAntically-cReaTed DOCuments) which aims at automatically generating webpages from RDF data. It will particularly focus on the current issues and the investigated solutions in the different modules of the project, which are related to document planning, natural language generation and multimedia perspectives. The second part of the talk will be dedicated to the KODA annotation system, which is a knowledge-base-agnostic annotator designed to provide the RDF annotations required in the document generation process.

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E-government / E-democracy
In what ways does the web change the ways we interact with government and change the ways we engage in politics?

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Foundations of Web Science: Introductory Lecture
An introduction to the "Foundations of Web Science" module that overviews the module itself, plus the context of web science at Southampton in terms of WSRI and the new Doctoral Training Centre.

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Foundations of Web Science: Introductory Lecture 2. What is Web Science?
Professor Nigel Shadbolt describes the emergence of Web Science Research Initiative and discusses the themes and topics that contribute to an understanding of Web Science.

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How the Web changes the World and universities (or not)
A look at how the technology of the Web has impacted Universities

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And 9 more...
INFO2009 2012-13 Resource Group 15 - Web Science
Web Science - Group 15 created an interactive infographic which informs prospective applicants about the new Web Science undergraduate degrees offered at the University of Southampton, starting in October 2013. Web Science as a new and exciting field of research is also briefly outlined, supported by two video interviews with Dr Les Car, a web scientist.

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Identity is the new Money
Three things to think about and Three possible futures to discuss

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Individuals, Behaviour Change and the Web
A psychologist's description of the Web as an effective channel for inducing and promoting changes of behaviour in individuals. Demonstrates an experimental system called "LifeGuide".

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Introduction to Network Mathematics
Introduction to Network Mathematics provides college students with basic graph theory to better understand the Internet

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Law, The Universe and Everything. The Regulation of the Web
Web Science lecture about the impact of law on the web and vice versa.

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And 5 more...
Looking at the Web Science 2009 Conference
The first International Conference on Web Science is taking place in Athens, concurrently with this course. The material here will allow you to get familiar with the conference presentations and posters so that you can write a summary of the conference from a particular topical perspective. (Both the attached HTML summaries are currently in draft form and need to have the preview images and metadata checked.)

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And 3 more...
Mapping the Web
Different attempts to 'map' different aspects of the web. How do you impose some sort of high level understanding onto the Web Graph?

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Mapping the Web and Web Science
This tutorial material introduces an activity in which the students are asked to redraw Tim Berners-Lee's map of the Web to include Web Science.

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Methods and Methodology: COMP6049
Slides and exercises for class on methods and methodology to web science masters. Explores inter-disciplinarity and disciplinary differences

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Networks 3: Social Structures
A brief look at the post-industrial, network society, freed from manual labour and liberated from place.

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Open Data
Profile PictureMiss Kewalin Angkananon
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Posters for Web Science DTC Industrial Day
These posters were created by Web Science MSc and PhD students as a discussion point with representatives from the DTC Industrial Advisory Group.

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Renssellaer Institute. Jim Hendler. CSCI 4964/COMM 49652 – Web Science. Social Network
Social Networks on the World Wide Web - lecture by Dr. Jennifer Golbeck

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Research on Social Network Sites
A bibliography of research on Social Network web sites. The research contained below is focused specifically on social network sites (or "social networking" sites). Some of this is connected to social media, social software, Web2.0, social bookmarking, educational technologies, communities research, etc. but this is not the organizing focus and not everything related to these other topics is included here. This list is not methodologically or disciplinarily organized. There is work here from communications, information science, anthropology, sociology, economics, political science, cultural studies, computer science, etc.

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Social Networks and Actors
A discussion about Actor Network Theory

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And 6 more...
Social Networks and Small World phenomena
Social Networking tools like Facebook yield recognisable small world phenomena, that is particular kinds of social graphs that facilitate particular kinds of interaction and information exchange.

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Study Skills: Precis and Argumentation
Society is catching up with the implications of the Web; its use is not straightforward and well-understood. Web Scientists will need to be able to handle arguments about equivocal perspectives on the Web's impact.

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 1
In this class, we will discuss the course organization and provide a basic motivation for and introduction to the course. Readings: Web science: a provocative invitation to computer science, B. Shneiderman, Communications of the ACM 50 25--27 (2007) [Web link] Readings: Chapter 1 & 2, A Framework for Web Science, T. Berners-Lee and W. Hall and J. A. Hendler and K. O'Hara and N. Shadbolt and D. J. Weitzner Foundations and Trends® in Web Science 1 (2006) [Web link] Originally from: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 10: Text Mining
This class introduces basics of web mining and information retrieval including, for example, an introduction to the Vector Space Model and Text Mining. Guest Lecturer: Dr. Michael Granitzer Optional: Modeling the Internet and the Web: Probabilistic Methods and Algorithms, Pierre Baldi, Paolo Frasconi, Padhraic Smyth, Wiley, 2003 (Chapter 4, Text Analysis)

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 11: User Intentions and Intentional Structures on the Web
Search engines - such as Google - have been characterized as "Databases of intentions". This class will focus on different aspects of intentionality on the web, including goal mining, goal modeling and goal-oriented search. Readings: M. Strohmaier, M. Lux, M. Granitzer, P. Scheir, S. Liaskos, E. Yu, How Do Users Express Goals on the Web? - An Exploration of Intentional Structures in Web Search, We Know'07 International Workshop on Collaborative Knowledge Management for Web Information Systems in conjunction with WISE'07, Nancy, France, 2007. [Web link] Readings: Automatic identification of user goals in web search, U. Lee and Z. Liu and J. Cho WWW '05: Proceedings of the 14th International World Wide Web Conference 391--400 (2005) [Web link]

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 12: User Intentions and Intentional Structures on the Web II
In this lecture, we will focus on analyzing user goals in search query logs. Readings: M. Strohmaier, P. Prettenhofer, M. Lux, Different Degrees of Explicitness in Intentional Artifacts - Studying User Goals in a Large Search Query Log, CSKGOI'08 International Workshop on Commonsense Knowledge and Goal Oriented Interfaces, in conjunction with IUI'08, Canary Islands, Spain, 2008.

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 13: Web Technologies 2 - The Semantic Web
The semantic web represents a current research effort to increase the capability of machines to make sense of content on the web. In this class, Peter Scheir will give a guest lecture on the basic principles underlying the semantic web vision, including RDF, OWL and other standards.

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 2: Small World Problem
We will discuss several examples and research efforts related to the small world problem and set the ground for our discussion of network theory and social network analysis. Readings: An Experimental Study of the Small World Problem, J. Travers and S. Milgram Sociometry 32 425-443 (1969) [Protected Access] Optional: The Strength of Weak Ties, M.S. Granovetter The American Journal of Sociology 78 1360--1380 (1973) [Protected Access] Optional: Worldwide Buzz: Planetary-Scale Views on an Instant-Messaging Network, J. Leskovec and E. Horvitz MSR-TR-2006-186. Microsoft Research, June 2007. [Web Link, the most recent and comprehensive study on the subject!] Originally from: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 3: Network Theory and Terminology
In this class, we will discuss network theory fundamentals, including concepts such as diameter, distance, clustering coefficient and others. We will also discuss different types of networks, such as scale-free networks, random networks etc. Readings: Graph structure in the Web, A. Broder and R. Kumar and F. Maghoul and P. Raghavan and S. Rajagopalan and R. Stata and A. Tomkins and J. Wiener Computer Networks 33 309--320 (2000) [Web link, Alternative Link] Optional: The Structure and Function of Complex Networks, M.E.J. Newman, SIAM Review 45 167--256 (2003) [Web link] Original course at: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 4: Social Network Analysis
What are fundamental entities in social networks and what information is contained in social graphs? We will discuss some selected concepts in social network analysis, such as one- and two mode networks, prestige and centrality, and cliques, clans and clubs. Readings: Web tool predicts election results and stock prices, J. Palmer, New Scientist, 07 February (2008) [Protected Access] Optional: Social Network Analysis, Methods and Applications, S. Wasserman and K. Faust (1994)

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 5: Affiliation Networks
How can we analyze and understand affiliation networks? In this class, we will discuss properties of affiliation networks and we will investigate the use of Galois lattices for the exploration of structural patterns in bi-partite graphs. Optional : L.C. Freeman and D.R. White. Using Galois Lattices to Represent Network Data. Sociological Methodology, (23):127--146, (1993)

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 6: Network Evolution and Process
In this class, we will discuss the nature of network evolution and some selected network processes. We will discuss graph generation algorithms that generate networks with different interesting characteristics. Optional : The Structure and Function of Complex Networks (chapter 8), M.E.J. Newman, SIAM Review 45 167--256 (2003); Optional: Emergence of Scaling in Random Networks, A.L. Barabasi and R. Albert, Science 286, 509 (1999)

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 7: Link Analysis and Search
What are ways of searching in graphs? In this class, we will discuss basics of link analysis, including Google's PageRank algorithm as an example. Readings: The PageRank Citation Ranking: Bringing Order to the Web, L. Page and S. Brin and R. Motwani and T. Winograd (1998) Stanford Tecnical Report

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 8: Web Technologies 1
This class focuses on a selected subset of web technologies that are of interest to the topics of this course. Readings: Chapter 5 "Representational State Transfer (REST)", in "Architectural Styles and the Design of Network-based Software Architecture", Roy Fielding, Dissertation, University of California Irvine, 2000 Optional: Chapter "Representational State Transfer (REST)" in "Pro PHP XML and Web Services", R. Richards 633--672, 2006

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TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 9: Metadata, Tagging and Folksonomies
In this class, we will discuss metadata as well as current phenomena such as tagging and folksonomies. Readings: Ontologies Are Us: A Unified Model of Social Networks and Semantics, P. Mika, International Semantic Web Conference, 522-536, 2005. [Web link] Optional: Folksonomies: power to the people, E. Quintarelli, ISKO Italy-UniMIB Meeting, (2005)

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The Age of Social Machines
Many of the most successful and important systems that impact our lives combine humans, data, and algorithms at Web Scale. These social machines are amalgamations of human and machine intelligence. This seminar will provide an update on SOCIAM, a five year EPSRC Programme Grant that seeks to gain a better understanding of social machines; how they are observed and constituted, how they can be designed and their fate determined. We will review how social machines can be of value to society, organisations and individuals. We will consider the challenges they present to our various disciplines.

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The End of the World Wide Web
Nothing lasts forever. The World Wide Web was an essential part of life for much of humantiy in the early 21st century, but these days few people even remember that it existed. Members of the Web Science research group will present several possible scenarios for how the Web, as we know it, could cease to be. This will be followed by an open discussion about the future we want for the Web and what Web Science should be doing today to help make that future happen, or at least avoid some of the bad ones.

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The Sociology of the Web
A sociologist's description of the Web as a socially constructed/discovered/encountered piece of technology.

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The Web Social
Sociology of the Internet and the Sociology of the Web

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Transparency & Privacy
The Transparency Agenda of the 2010/1 UK Coalition government promises to revolutionise government, public services and public engagement, by ‘holding politicians and public bodies to account, reducing the deficit and delivering better value for money in public spending, and realising significant economic benefits by enabling businesses and non-profit organisations to build innovative applications and websites using public data’, to quote the then Prime Minister. This is an ambitious programme with laudable aims, yet it naturally has limits.

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User-Centred Methods for Measuring the Value of Open Data
A project to identify metrics for assessing the quality of open data based on the needs of small voluntary sector organisations in the UK and India. For this project we assumed the purpose of open data metrics is to determine the value of a group of open datasets to a defined community of users. We adopted a much more user-centred approach than most open data research using small structured workshops to identify users’ key problems and then working from those problems to understand how open data can help address them and the key attributes of the data if it is to be successful. We then piloted different metrics that might be used to measure the presence of those attributes. The result was six metrics that we assessed for validity, reliability, discrimination, transferability and comparability. This user-centred approach to open data research highlighted some fundamental issues with expanding the use of open data from its enthusiast base.

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W3233 -- Networks and Complexity in Social Systems (Collective Dynamics Group ISERP -- Columbia University) Course Syllabus
The Networks and Complexity in Social Systems course commences with an overview of the nascent field of complex networks, dividing it into three related but distinct strands: Statistical description of large scale networks, viewed as static objects; the dynamic evolution of networks, where now the structure of the network is understood in terms of a growth process; and dynamical processes that take place on fixed networks; that is, "networked dynamical systems". (A fourth area of potential research ties all the previous three strands together under the rubric of co-evolution of networks and dynamics, but very little research has been done in this vein and so it is omitted.) The remainder of the course treats each of the three strands in greater detail, introducing technical knowledge as required, summarizing the research papers that have introduced the principal ideas, and pointing out directions for future development. With regard to networked dynamical systems, the course treats in detail the more specific topic of information propagation in networks, in part because this topic is of great relevance to social science, and in part because it has received the most attention in the literature to date.

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What is Cybercrime and what do we do about?
A guest lecture by Professor David S.Wall from the University of Durham. This talk will explore the way that networked technology has transformed criminal behaviour. The first part will map out cybercrimes and identify the challenges they pose for both criminologists and also regulators. The second part will show that cybercrimes are informational, networked and global. In this section it will also be shown that cybercrimes are highly disorganised forms of offending when compared to the organisation of more 'traditional' crimes, but display some new organisational logics of their own. The third part of the talk will illustrate how the 'culture of fear' that has arisen around cybercrime has placed demands upon government and police - demands that, for reasons related to the distinct nature of cybercrimes, are hard to resolve. The fourth and final part will look at the new policing arrangements that are designed, it is argued here, to close the reassurance gap.

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And 4 more...
What is the Web? The Web Architecture
The Introductory Lecture is a discussion about "What is the Web". It involves lots of calling out TLAs and writing them on the blackboard, dividing things into servers, clients, protocols, formats, and the punchline is that the one unique and novel thing about the web is the hypertext link. This follows naturally into the Web architecture - the answer to the question "what is the web".

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What’s the Difference between Web Technology and Web Science? Opportunities for study and research at the University of Southampton
The University of Southampton has a long history of pursuing research, development and social change with the Web This document guides you through the opportunities for Web-related study and research that we offer: an MSc in Web Technology; a 3-year PhD in Web Technology; an MSc in Web Science or a 4-year PhD in Web Science

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And 2 more...
Who Invented the Web?
It is received wisdom that Tim Berners-Lee invented the Web; but there is a lot more technology and historical context that plays a part.

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jhofman's data and networks Bookmarks on Delicious
A list of many network datasets

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This list was generated on Sat May 30 15:38:19 2015 BST.