A Ranking Approach to Summarising Twitter Home Timelines

The rise of social media services has changed the ways in which users can communicate and consume content online. Whilst online social networks allow for fast and convenient delivery of knowledge, users are prone to information overload when too much information is presented for them to read and process. Automatic text summarisation is a tool to help mitigate information overload. In automatic text summarisation, short summaries are generated algorithmically from extended text, such as news articles or scientific papers. This thesis addresses the challenges in applying text summarisation to the Twitter social network. It also goes beyond text, exploiting additional information that is unique to social networks to create summaries which are personal to an intended reader. Unlike previous work in tweet summarisation, the experiments here address the home timelines of readers, which contain the incoming posts from authors to whom they have explicitly subscribed. A novel contribution is made in this work the form of a large gold standard ($19,350$ tweets), the majority of which will be shared with the research community. The gold standard is a collection of timelines that have been subjectively annotated by the readers to whom they belong, allowing fair evaluation of summaries which are not limited to tweets of general interest, but which are specific to the reader. Where the home timeline is used by professional users for social media analysis, automatic text summarisation can be applied to give results which beat all baselines. In the general case, where no limitation is placed on the types of readers, personalisation features which exploit the relationship between author and reader and the reader's own previous posts, were shown to outperform both automatic text summarisation and all baselines

Trends in European Climate Change Perception: Where the Effects of Climate Change go unnoticed

Climate change threatens global impacts in a variety of domains that must be limited by adaptation and mitigation measures. The successful implementation of such policies can strongly benefit from the general public’s cooperation motivated by their own risk perceptions. Public participation can be promoted by tailoring policies to the populations they affect, which in turn results in the need for a deeper understanding of how different communities interact with the issue of climate change. Social media platforms such as the microblogging service Twitter have opened unprecedented opportunities for research on public perception in recent years, offering a continuous stream of user-generated data. Simultaneously, they represent a crucial discursive space in which members of the public develop and discuss their opinions and concerns about climate change. Subsequently, this thesis gains insight into the characteristics of public reactions to individual climate change effects and processes by investing corresponding corpora of tweets spanning a decade. For seven western European countries, the spatial, temporal, and thematic reaction patterns are determined with a further assessment of the drivers behind each finding. Tweets are collected, classified, georeferenced, and clustered using a selection of Geographic Information Retrieval as well as Natural Language Processing methods before being analysed regarding thematic trends in their content, spatial distributions and influences of environmental factors, as well temporal distributions and impacts of real-world events. The findings illustrate diverse climate change perceptions that vary across spatial, temporal, and thematic dimensions. Communities tend to focus more on issues relevant to their local or national environment, leading populations to develop a certain degree of specialisation for these aspects of climate change. This typically coincides with a substantially more domestic discourse on the subject and a decrease in interest for corresponding international events. In a similar sense, the tangibility of an event drives the magnitude of reactions. However, while more tangible events are more frequently recognised and discussed, less tangible events tend to be more frequently attributed to climate change as the public shifts their focus from immediate impacts on the personal scale to impacts on the global scale. Additionally, traditional news media are shown to retain a high level of control over science communication and the climate change discourse on Twitter, likely influencing the public’s perspective on global warming. Individual real-world events such as major climate conferences and scientific releases only occasionally elicit strong public reactions when they are topically related to an event type, whereas global protests can lead to significant discussion across various event types. Inversely, global crises such as the COVID-19 pandemic significantly reduce public concern about climate change processes

AC+erm – 'Accelerating positive change in electronic records management'

This project critically explored issues and practical strategies to support accelerating the pace of positive change in managing electronic records (ERM). Its focus was on designing an organisation-centred architecture from three perspectives: 1. people including vision, awareness, culture, drivers and barriers 2. working practices including processes, procedures, policies and standards 3. technology in terms of the design principles for delivering effective recordkeeping. The investigation considered what (if any) vision organisations had for their office environment; their vision of recordkeeping in the context of their mission; the drivers and influencers for ERM (e.g. risk management, compliance, corporate governance), and the barriers to implementing ERM. It used a novel combination of methods (systematic literature review, virtual Delphi Studies, and our face-to-face colloquia) and a blog to disseminate ideas and findings regularly to the widest possible audience (http://acerm.blogspot.co.uk/). The project ran from 2007-2010 and was funded by the Arts & Humanities Research Council, UK. Project outputs are freely available at the related link below. Note: AC+erm is pronounced āsirm; the + is silent, and simply indicates that positive change

Inferring interestingness in online social networks

Information sharing and user-generated content on the Internet has given rise to the increased presence of uninteresting and ‘noisy’ information in media streams on many online social networks. Although there is a lot of ‘interesting’ information also shared amongst users, the noise increases the cognitive burden in terms of the users’ abilities to identify what is interesting and may increase the chance of missing content that is useful or important. Additionally, users on such platforms are generally limited to receiving information only from those that they are directly linked to on the social graph, meaning that users exist within distinct content ‘bubbles’, further limiting the chance of receiving interesting and relevant information from outside of the immediate social circle. In this thesis, Twitter is used as a platform for researching methods for deriving “interestingness” through popularity as given by the mechanism of retweeting, which allows information to be propagated further between users on Twitter’s social graph. Retweet behaviours are studied, and features; such as those surrounding Tweet audience, information redundancy, and propagation depth through path-length, are uncovered to help relate retweet action to the underlying social graph and the communities it represents. This culminates in research into a methodology for assigning scores to Tweets based on their ‘quality’, which is validated and shown to perform well in various situations

Decoding learning: the proof, promise and potential of digital education

With hundreds of millions of pounds spent on digital technology for education every year – from interactive whiteboards to the rise of one–to–one tablet computers – every new technology seems to offer unlimited promise to learning. many sectors have benefitted immensely from harnessing innovative uses of technology. cloud computing, mobile communications and internet applications have changed the way manufacturing, finance, business services, the media and retailers operate. But key questions remain in education: has the range of technologies helped improve learners’ experiences and the standards they achieve? or is this investment just languishing as kit in the cupboard? and what more can decision makers, schools, teachers, parents and the technology industry do to ensure the full potential of innovative technology is exploited? There is no doubt that digital technologies have had a profound impact upon the management of learning. institutions can now recruit, register, monitor, and report on students with a new economy, efficiency, and (sometimes) creativity. yet, evidence of digital technologies producing real transformation in learning and teaching remains elusive. The education sector has invested heavily in digital technology; but this investment has not yet resulted in the radical improvements to learning experiences and educational attainment. in 2011, the Review of Education Capital found that maintained schools spent £487 million on icT equipment and services in 2009-2010. 1 since then, the education system has entered a state of flux with changes to the curriculum, shifts in funding, and increasing school autonomy. While ring-fenced funding for icT equipment and services has since ceased, a survey of 1,317 schools in July 2012 by the british educational suppliers association found they were assigning an increasing amount of their budget to technology. With greater freedom and enthusiasm towards technology in education, schools and teachers have become more discerning and are beginning to demand more evidence to justify their spending and strategies. This is both a challenge and an opportunity as it puts schools in greater charge of their spending and use of technolog

Impact Evaluation of the Spanish Citizens' Climate Assembly.

The Spanish Citizens´ Climate Assembly (SCCA) started in November 2021 and concluded in May 2022. This report aims to evaluate the SCCA´s impact across different areas, including policy, assembly members’ attitudes, public engagement, and the media. To guide this evaluation, we employed the Impact Evaluation Framework (IEF) developed byChristina Demski and Stuart Capstick of the Centre for Climate Change and Social Transformations (CAST) for the Knowledge Network of Climate Assemblies (KNOCA). The IEF can be downloaded from the KNOCA website. 1 Our research strategy relied on methodological triangulation, incorporating various means of data collection, including: opinion surveys (among assembly members, the general population, and political representatives and policymakers), qualitative interviews (with organisers, assembly members, public servants, and recognised experts), document analysis, and a systematic examination of digital and social media.European Climate Foundation (ECF_2209-64626

The social outcomes of psychosocial support:A grey literature scoping review

Contains fulltext : 246920.pdf (Publisher’s version ) (Open Access)Policymakers, practitioners and academics expect mental health and psychosocial support (MHPSS) interventions to have social outcomes. Surprisingly, the existing academic literature on the effectiveness of MHPSS has focused almost exclusively on clinical outcomes. The evidence base of MHPSS interventions is in that way limited. To feed the research agenda on MHPSS (i.e., MHPSS-SET2), this scoping review analyses the presence and understanding of social outcomes in the grey literature. Open-access documents were systematically searched from various online grey literature databases and websites of organisations. Documents which describe psychosocial programming in low- and middle-income countries for people affected by humanitarian emergencies were included. Data characteristics were extracted, such as the type of document, intervention and outcome. A textual analysis of social outcomes was conducted to categorise the descriptions of these outcomes. A total number of 95 grey literature documents were included in the review. It was found that in the vast majority of the reviewed documents, social outcomes are being described. However, social outcomes have been poorly conceptualised both theoretically and methodologically, meaning that most documents lack definitions of theoretical concepts and measurement instruments. Mechanisms relating interventions to social outcomes have remained implicit. These findings are interpreted in light of key developments in the field of MHPSS, in particular the introduction of the Inter-Agency Standing Committee (IASC) guidelines, and the review traces the underexposed position of social outcomes back to the clinical historical roots of the field. In conclusion, those who develop and evaluate interventions should focus more structural attention on social outcomes to fully understand the possible impact of psychosocial interventions. Further harmonisation between academic research and practice is necessary, by drawing from practice-based insights on social outcomes as found in the grey literature, and using methods and measurement instruments from social sciences in MHPSS research.14 p

A visual analytics approach for visualisation and knowledge discovery from time-varying personal life data

A thesis submitted to the University of Bedfordshire, in ful filment of the requirements for the degree of Doctor of PhilosophyToday, the importance of big data from lifestyles and work activities has been the focus of much research. At the same time, advances in modern sensor technologies have enabled self-logging of a signi cant number of daily activities and movements. Lifestyle logging produces a wide variety of personal data along the lifespan of individuals, including locations, movements, travel distance, step counts and the like, and can be useful in many areas such as healthcare, personal life management, memory recall, and socialisation. However, the amount of obtainable personal life logging data has enormously increased and stands in need of effective processing, analysis, and visualisation to provide hidden insights owing to the lack of semantic information (particularly in spatiotemporal data), complexity, large volume of trivial records, and absence of effective information visualisation on a large scale. Meanwhile, new technologies such as visual analytics have emerged with great potential in data mining and visualisation to overcome the challenges in handling such data and to support individuals in many aspects of their life. Thus, this thesis contemplates the importance of scalability and conducts a comprehensive investigation into visual analytics and its impact on the process of knowledge discovery from the European Commission project MyHealthAvatar at the Centre for Visualisation and Data Analytics by actively involving individuals in order to establish a credible reasoning and effectual interactive visualisation of such multivariate data with particular focus on lifestyle and personal events. To this end, this work widely reviews the foremost existing work on data mining (with the particular focus on semantic enrichment and ranking), data visualisation (of time-oriented, personal, and spatiotemporal data), and methodical evaluations of such approaches. Subsequently, a novel automated place annotation is introduced with multilevel probabilistic latent semantic analysis to automatically attach relevant information to the collected personal spatiotemporal data with low or no semantic information in order to address the inadequate information, which is essential for the process of knowledge discovery. Correspondingly, a multi-signi ficance event ranking model is introduced by involving a number of factors as well as individuals' preferences, which can influence the result within the process of analysis towards credible and high-quality knowledge discovery. The data mining models are assessed in terms of accurateness and performance. The results showed that both models are highly capable of enriching the raw data and providing significant events based on user preferences. An interactive visualisation is also designed and implemented including a set of novel visual components signifi cantly based upon human perception and attentiveness to visualise the extracted knowledge. Each visual component is evaluated iteratively based on usability and perceptibility in order to enhance the visualisation towards reaching the goal of this thesis. Lastly, three integrated visual analytics tools (platforms) are designed and implemented in order to demonstrate how the data mining models and interactive visualisation can be exploited to support different aspects of personal life, such as lifestyle, life pattern, and memory recall (reminiscence). The result of the evaluation for the three integrated visual analytics tools showed that this visual analytics approach can deliver a remarkable experience in gaining knowledge and supporting the users' life in certain aspects

Designing social media analytics tools to support non-market institutions: Four case studies using Twitter data

This research investigates the design of social media tools for non-market institutions, such as local government or community groups. At the core of this practice-based research is a software tool called LocalNets. LocalNets was developed to collect, analyse and visualise data from Twitter, thereby revealing information about community structure and community assets. It is anticipated that this information could help non- market institutions and the communities with which they work. Twitter users send messages to one another using the ‘@mention’ function. This activity is made visible publicly and has the potential to indicate a Twitter user’s participation in a ‘community structure’; that is, it can reveal an interpersonal network of social connections. Twitter activity also provides data about community assets (such as parks, shops and cinemas) when tweets mention these assets’ names. The context for this research is the Creative Exchange Hub (CX), one of four Knowledge Exchange Hubs for the Creative Economy funded by the UK Arts and Humanities Research Council (AHRC). Under the theme of ‘Digital Public Space’, the CX Hub facilitated creative research collaborations between PhD researchers, academics and non-academic institutions. Building on the CX model, this PhD research forged partnerships between local councils, non-public sector institutions that work with communities, software developers and academics with relevant subject expertise. Development of the LocalNets tool was undertaken as an integral part of the research. As the software was developed, it was deployed in relevant contexts through partnerships with a range of non-market institutions, predominantly located in the UK, to explore its use in those contexts. Four projects are presented as design case studies: 1) a prototyping phase, 2) a project with the Royal Society of Arts in the London Borough of Hounslow, 3) a multi-partner project in Peterborough, and 4) a project with Newspeak House, a technology and politics co-working space located in London. The case studies were undertaken using an Action Design Research method, as articulated by Sein et al. Findings from these case studies are grouped into two categories. The first are ‘Implementation findings’ which relate specifically to the use of data from Twitter. Second there are six ‘situated design principles’ which were developed across the case studies, and which are proposed as having potential application beyond Twitter data. The ‘Implementation findings’ include that Twitter can be effective for locating participants for focus groups on community topics, and that the opinions expressed directly in tweets are rarely sufficient for the local government of community groups to respond to. These findings could benefit designers working with Twitter data. The six situated design principles were developed through the case studies: two apply Burt’s brokerage social capital theory, describing how network structure relates to social capital; two apply Donath’s signalling theory – which suggests how social media behaviours can indicate perceptions of community assets; and two situated design principles apply Borgatti and Halgin’s network flow model – a theory which draws together brokerage social capital and signalling theory. The principles are applicable to social media analytics tools and are relevant to the goals of non-market institutions. They are situated in the context of the case studies; however, they are potentially applicable to social media platforms other than Twitter. Linders identifies a paucity of research into social media tools for non-market institutions. The findings of this research, developed by deploying and testing the LocalNets social media analytics tool with non-market institutions, aim to address that research gap and to inform practitioner designers working in this area