MACE: Joint Deliverable "Evaluation of the MACE system"

Stefaner, M., Wolpers, M., Memmel, M., Duval, E., Specht, M., Börner, D., Gruber, M., De Jong, T., Giretti, A., & Klemke, R. (2009). MACE: Joint Deliverable "Evaluation of the MACE system". MACE-project.This deliverable presents the evaluation results of the MACE project1. MACE integrates large amounts of technology enhanced learning contents and metadata in the domain of architecture, in order to create a framework for the integration of multiple content sources, content enrichment with different metadata types, and improved access to these existing contents.MAC

BlogForever: D3.1 Preservation Strategy Report

This report describes preservation planning approaches and strategies recommended by the BlogForever project as a core component of a weblog repository design. More specifically, we start by discussing why we would want to preserve weblogs in the first place and what it is exactly that we are trying to preserve. We further present a review of past and present work and highlight why current practices in web archiving do not address the needs of weblog preservation adequately. We make three distinctive contributions in this volume: a) we propose transferable practical workflows for applying a combination of established metadata and repository standards in developing a weblog repository, b) we provide an automated approach to identifying significant properties of weblog content that uses the notion of communities and how this affects previous strategies, c) we propose a sustainability plan that draws upon community knowledge through innovative repository design

BlogForever D2.6: Data Extraction Methodology

This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform

Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing

Near Real-Time Sentiment and Topic Analysis of Sport Events

Sport events’ media consumption patterns have started transitioning to a multi-screen paradigm, where, through multitasking, viewers are able to search for additional information about the event they are watching live, as well as contribute with their perspective of the event to other viewers. The audiovisual and multimedia industries, however, are failing to capitalize on this by not providing the sports’ teams and those in charge of the audiovisual production with insights on the final consumers perspective of sport events. As a result of this opportunity, this document focuses on presenting the development of a near real-time sentiment analysis tool and a near real-time topic analysis tool for the analysis of sports events’ related social media content that was published during the transmission of the respective events, thus enabling, in near real-time, the understanding of the sentiment of the viewers and the topics being discussed through each event.Os padrões de consumo de media, têm vindo a mudar para um paradigma de ecrãs múltiplos, onde, através de multitasking, os telespetadores podem pesquisar informações adicionais sobre o evento que estão a assistir, bem como partilhar a sua perspetiva do evento. As indústrias do setor audiovisual e multimédia, no entanto, não estão a aproveitar esta oportunidade, falhando em fornecer às equipas desportivas e aos responsáveis pela produção audiovisual uma visão sobre a perspetiva dos consumidores finais dos eventos desportivos. Como resultado desta oportunidade, este documento foca-se em apresentar o desenvolvimento de uma ferramenta de análise de sentimento e uma ferramenta de análise de tópicos para a análise, em perto de tempo real, de conteúdo das redes sociais relacionado com eventos esportivos e publicado durante a transmissão dos respetivos eventos, permitindo assim, em perto de tempo real, perceber o sentimento dos espectadores e os tópicos mais falados durante cada evento

Learning from Digital Natives: Bridging Formal and Informal Learning. Final Report

Overview This report suggests that students are increasingly making use of a variety of etools (such as mobile phones, email, MSN, digital cameras, games consoles and social networking sites) to support their informal learning within formalised educational settings, and that they use the tools that they have available if none are provided for them. Therefore, higher education institutions should encourage the use of these tools. Aims and background This study aimed to explore how e-tools (such as mobile phones, email, MSN, digital cameras, games consoles and social networking sites) and the processes that underpin their use can support learning within educational institutions and help improve the quality of students’ experiences of learning in higher education (pgs 9-11). Methodology The study entailed: (i) desk research to identify related international research and practice and examples of integration of e-tools and learning processes in formal educational settings; (ii) a survey of 160 engineering and social work students across two contrasting Scottish universities (pre- and post-1992) – the University of Strathclyde and Glasgow Caledonian University – and follow-up interviews with eight students across the two subject areas to explore which technologies students were using for both learning and leisure activities within and outside the formal educational settings and how they would like to use such technologies to support their learning in both formal and informal settings; and (iii) interviews with eight members of staff from across the institutions and two subject areas to identify their perceptions of the educational value of the e-tools. (pgs 24-27). Key findings • Students reported making extensive use of a variety of both e-tools (such as mobile phones, email, MSN, digital cameras) and social networking tools (such as Bebo, MySpace, Wikipedia and YouTube) for informal socialisation, communication, information gathering, content creation and sharing, alongside using the institutionally provided technologies and learning environments. • Most of the students owned their own computer or had access to a sibling or parent’s computer. Many students owned a laptop but preferred not to bring it onto campus due to security concerns and because they found it too heavy to carry about. • Ownership of mobile phones was ubiquitous. • Whilst the students’ information searching literacy seemed adequate, the ability of these students to harness the power of social networking tools and informal processes for their learning was low. Staff reported using a few Web 2.0 and social software tools but they were generally less familiar with how these could be used to support learning and teaching. There were misconceptions surrounding the affordances of the tools and fears expressed about security and invasion of personal space. Considerations of the costs and the time it would take staff to develop their skills meant that there was a reluctance to take up new technologies at an institutional level. • Subject differences emerged in both staff and student perceptions as to which type of tools they would find most useful. Attitudes to Web 2.0 tools were different. Engineers were concerned with reliability, using institutional systems and inter-operability. Social workers were more flexible because they were focused on communication and professional needs. • The study concluded that digital tools, personal devices, social networking software and many of the other tools explored all have a large educational potential to support learning processing and teaching practices. Therefore, use of these tools and processes within institutions, amongst staff and students should be encouraged. • The report goes on to suggest ways in which the use of such technologies can help strengthen the links between informal and formal learning in higher education. The recommendations are grouped under four areas – pedagogical, socio-cultural, organisational and technological

Supporting exploratory browsing with visualization of social interaction history

This thesis is concerned with the design, development, and evaluation of information visualization tools for supporting exploratory browsing. Information retrieval (IR) systems currently do not support browsing well. Responding to user queries, IR systems typically compute relevance scores of documents and then present the document surrogates to users in order of relevance. Other systems such as email clients and discussion forums simply arrange messages in reverse chronological order. Using these systems, people cannot gain an overview of a collection easily, nor do they receive adequate support for finding potentially useful items in the collection. This thesis explores the feasibility of using social interaction history to improve exploratory browsing. Social interaction history refers to traces of interaction among users in an information space, such as discussions that happen in the blogosphere or online newspapers through the commenting facility. The basic hypothesis of this work is that social interaction history can serve as a good indicator of the potential value of information items. Therefore, visualization of social interaction history would offer navigational cues for finding potentially valuable information items in a collection. To test this basic hypothesis, I conducted three studies. First, I ran statistical analysis of a social media data set. The results showed that there were positive relationships between traces of social interaction and the degree of interestingness of web articles. Second, I conducted a feasibility study to collect initial feedback about the potential of social interaction history to support information exploration. Comments from the participants were in line with the research hypothesis. Finally, I conducted a summative evaluation to measure how well visualization of social interaction history can improve exploratory browsing. The results showed that visualization of social interaction history was able to help users find interesting articles, to reduce wasted effort, and to increase user satisfaction with the visualization tool

Syntactic and Semantic Analysis and Visualization of Unstructured English Texts

People have complex thoughts, and they often express their thoughts with complex sentences using natural languages. This complexity may facilitate efficient communications among the audience with the same knowledge base. But on the other hand, for a different or new audience this composition becomes cumbersome to understand and analyze. Analysis of such compositions using syntactic or semantic measures is a challenging job and defines the base step for natural language processing. In this dissertation I explore and propose a number of new techniques to analyze and visualize the syntactic and semantic patterns of unstructured English texts. The syntactic analysis is done through a proposed visualization technique which categorizes and compares different English compositions based on their different reading complexity metrics. For the semantic analysis I use Latent Semantic Analysis (LSA) to analyze the hidden patterns in complex compositions. I have used this technique to analyze comments from a social visualization web site for detecting the irrelevant ones (e.g., spam). The patterns of collaborations are also studied through statistical analysis. Word sense disambiguation is used to figure out the correct sense of a word in a sentence or composition. Using textual similarity measure, based on the different word similarity measures and word sense disambiguation on collaborative text snippets from social collaborative environment, reveals a direction to untie the knots of complex hidden patterns of collaboration