Towards a general framework for social media research using big data

The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a general-purpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.

Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.

Young People, Peer-to-Peer Grooming and Sexual Offending: Understanding and Responding to Harmful Sexual Behaviour within a Social Media Society

There is ample evidence that young people engage in grooming and harmful sexual behaviour (HSB) using social media with enough frequency to make those behaviours important con-cerns for both society and care providers. This article provides a critical overview of the con-ceptual and empirical foundations of peer-to-peer grooming and the use of social media with-in the context of HSB. Based on this learning, it ultimately introduces a new model of inter-vention and of professional practice, which provides the standards for micro-level decision-making about goals, methods and assessment tailored to this specific offending context.

Improved lexicon-based sentiment analysis for social media analytics

Social media channels, such as Facebook or Twitter, allow for people to express their views and opinions about any public topics. Public sentiment related to future events, such as demonstrations or parades, indicate public attitude and therefore may be applied while trying to estimate the level of disruption and disorder during such events. Consequently, sentiment analysis of social media content may be of interest for different organisations, especially in security and law enforcement sectors. This paper presents a new lexicon-based sentiment analysis algorithm that has been designed with the main focus on real time Twitter content analysis. The algorithm consists of two key components, namely sentiment normalisation and evidence-based combination function, which have been used in order to estimate the intensity of the sentiment rather than positive/negative label and to support the mixed sentiment classification process. Finally, we illustrate a case study examining the relation between negative sentiment of twitter posts related to English Defence League and the level of disorder during the organisation’s related events.

Extending Customer Relationship Management into a Social Context

Informed by the resource-based view, this study draws on customer relationship management (CRM) and value co-creation literature to develop a framework examining the impact of social networking sites on processes to manage customer relationships. Facilitating the depth and networked interactions necessary to truly engage customers, social networking sites act as a means of enhancing customer relationships through the co-creation of value, moving CRM into a social context. Tested and validated on a data set of hotels, the main contribution of the study to service research lies in the extension of CRM processes, termed relational information processes, to include value co-creation processes due to the social capabilities afforded by social networking sites. Information technology competency and social media orientation act as critical antecedents to these processes, which have a positive impact on both financial and non-financial aspects of firm performance. The theoretical and managerial implications of these findings are discussed accordingly.

Community Relations in Northern Ireland: a shift in Attitudes?

The paper presents an analysis of Northern Ireland Social Attitudes data available at the time of writing. Its significance lay in emerging disparities in the responses, over time, of Protestants and Catholics to key social issues such as integrated education. The data, made public just one year after the signing of the Belfast/Good Friday Agreement, generated intense media interest. Findings were reported in 400 outlets worldwide (UU media monitoring). Hughes was also interviewed for local and national news programmes (including BBC World Service). The data informed a decision by Government to undertake a major review of community relations policy, and Hughes was invited to advise the Head of the Northern Ireland review team. She was also invited to Chair the Community Relations Panel of the ESRC Devolution

The rise of the digital citizen-stakeholder: rebalancing multistakeholder governance

The principle feature in the evolution of the internet has been its ever growing reach to include old and young, rich and poor. The internet’s ever encroaching presence has transported it from our desktop to our pocket and into our glasses. This is illustrated in the Internet Society Questionnaire on Multistakeholder Governance, which found the main factors affecting change in the Internet governance landscape were more users online from more countries and the influence of the internet over daily life. The omnipresence of the internet is self- perpetuating; its usefulness grows with every new user and every new piece of data uploaded. The advent of social media and the creation of a virtual presence for each of us, even when we are not physically present or ‘logged on’, means we are fast approaching the point where we are all connected, to everyone else, all the time. We have moved far beyond the point where governments can claim to represent our views which evolve constantly rather than being measured in electoral cycles.
The shift, which has seen citizens as creators of content rather than consumers of it, has undermined the centralist view of democracy and created an environment of wiki democracy or crowd sourced democracy. This is at the heart of what is generally known as Web 2.0, and widely considered to be a positive, democratising force. However, we argue, there are worrying elements here too. Government does not always deliver on the promise of the networked society as it involves citizens and others in the process of government. Also a number of key internet companies have emerged as powerful intermediaries harnessing the efforts of the many, and re- using and re-selling the products and data of content providers in the Web 2.0 environment. A discourse about openness and transparency has been offered as a democratising rationale but much of this masks an uneven relationship where the value of online activity flows not to the creators of content but to those who own the channels of communication and the metadata that they produce.
In this context the state is just one stakeholder in the mix of influencers and opinion formers impacting on our behaviours, and indeed our ideas of what is public. The question of what it means to create or own something, and how all these new relationships to be ordered and governed are subject to fundamental change. While government can often appear slow, unwieldy and even irrelevant in much of this context, there remains a need for some sort of political control to deal with the challenges that technology creates but cannot by itself control. In order for the internet to continue to evolve successfully both technically and socially it is critical that the multistakeholder nature of internet governance be understood and acknowledged, and perhaps to an extent, re- balanced. Stakeholders can no longer be classified in the broad headings of government, private sector and civil society, and their roles seen as some sort of benign and open co-production. Each user of the internet has a stake in its efficacy and each by their presence and participation is contributing to the experience, positive or negative of other users as well as to the commercial success or otherwise of various online service providers. However stakeholders have neither an equal role nor an equal share. The unequal relationship between the providers of content and those who simple package up and transmit that content - while harvesting the valuable data thus produced - needs to be addressed. Arguably this suggests a role for government that involves it moving beyond simply celebrating and facilitating the on- going technological revolution. This paper reviews the shifting landscape of stakeholders and their contribution to the efficacy of the internet. It will look to critically evaluate the primacy of the individual as the key stakeholder and their supposed developing empowerment within the ever growing sea of data. It also looks at the role of individuals in wider governance roles. Governments in a number of jurisdictions have sought to engage, consult or empower citizens through technology but in general these attempts have had little appeal. Citizens have been too busy engaging, consulting and empowering each other to pay much attention to what their governments are up to. George Orwell’s view of the future has not come to pass; in fact the internet has insured the opposite scenario has come to pass. There is no big brother but we are all looking over each other’s shoulder all the time, while at the same time a number of big corporations are capturing and selling all this collective endeavour back to us.

Knowledge Management Techniques to Augment Textual CBR (PhD Thesis)

The past decade had witnessed an unprecedented growth in the amount of available digital content, and its volume is expected to continue to grow the next few years. Unstructured text data generated from web and enterprise sources form a large fraction of such content. Many of these contain large volumes of reusable data such as solutions to frequently occurring problems, and general know-how that may be reused in appropriate contexts. In this work, we address issues around leveraging unstructured text data from sources as diverse as the web and the enterprise within the Case-based Reasoning framework. Case-based Reasoning (CBR) provides a framework and methodology for systematic reuse of historical knowledge that is available in the form of problemsolution
pairs, in solving new problems. Here, we consider possibilities of enhancing Textual CBR systems under three main themes: procurement, maintenance and retrieval. We adapt and build upon the stateof-the-art techniques from data mining and natural language processing in addressing various challenges therein. Under procurement, we investigate the problem of extracting cases (i.e., problem-solution pairs) from data sources such as incident/experience
reports. We develop case-base maintenance methods specifically tuned to text targeted towards retaining solutions such that the utility of the filtered case base in solving new problems is maximized. Further, we address the problem of query suggestions for textual case-bases and show that exploiting the problem-solution partition can enhance retrieval effectiveness by prioritizing more useful query suggestions. Additionally, we illustrate interpretable clustering as a tool to drill-down to domain specific text collections (since CBR systems are usually very domain specific) and develop techniques for improved similarity assessment in social media sources such as microblogs. Through extensive empirical evaluations, we illustrate the improvements that we are able to
achieve over the state-of-the-art methods for the respective tasks.

A Machine Learning Analysis of Twitter Sentiment to the Sandy Hook Shootings

Gun related violence is a complex issue and accounts for a large proportion of violent incidents. In the research reported in this paper, we set out to investigate the pro-gun and anti-gun sentiments expressed on a social media platform, namely Twitter, in response to the 2012 Sandy Hook Elementary School shooting in Connecticut, USA. Machine learning techniques are applied to classify a data corpus of over 700,000 tweets. The sentiments are captured using a public sentiment score that considers the volume of tweets as well as population. A web-based interactive tool is developed to visualise the sentiments and is available at this http://www.gunsontwitter.com. The key findings from this research are: (i) There are elevated rates of both pro-gun and anti-gun sentiments on the day of the shooting. Surprisingly, the pro-gun sentiment remains high for a number of days following the event but the anti-gun sentiment quickly falls to pre-event levels. (ii) There is a different public response from each state, with the highest pro-gun sentiment not coming from those with highest gun ownership levels but rather from California, Texas and New York.

Systematic evaluation of patient-reported outcome (PRO) protocol content and reporting in UK cancer clinical trials: the EPiC study protocol

Introduction Emerging evidence suggests that patient-reported outcome (PRO)-specific information may be omitted in trial protocols and that PRO results are poorly reported, limiting the use of PRO data to inform cancer care. This study aims to evaluate the standards of PRO-specific content in UK cancer trial protocols and their arising publications and to highlight examples of best-practice PRO protocol content and reporting where they occur. The objective of this study is to determine if these early findings are generalisable to UK cancer trials, and if so, how best we can bring about future improvements in clinical trials methodology to enhance the way PROs are assessed, managed and reported. Hypothesis: Trials in which the primary end point is based on a PRO will have more complete PRO protocol and publication components than trials in which PROs are secondary end points.

Methods and analysis Completed National Institute for Health Research (NIHR) Portfolio Cancer clinical trials (all cancer specialities/age-groups) will be included if they contain a primary/secondary PRO end point. The NIHR portfolio includes cancer trials, supported by a range of funders, adjudged as high-quality clinical research studies. The sample will be drawn from studies completed between 31 December 2000 and 1 March 2014 (n=1141) to allow sufficient time for completion of the final trial report and publication. Two reviewers will then review the protocols and arising publications of included trials to: (1) determine the completeness of their PRO-specific protocol content; (2) determine the proportion and completeness of PRO reporting in UK Cancer trials and (3) model factors associated with PRO protocol and reporting completeness and with PRO reporting proportion.

Ethics and dissemination The study was approved by the ethics committee at University of Birmingham (ERN_15-0311). Trial findings will be disseminated via presentations at local, national and international conferences, peer-reviewed journals and social media including the CPROR twitter account and UOB departmental website (http://www.birmingham.ac.uk/cpro0r).