A simple Bayesian modelling approach to event extraction from Twitter

With the proliferation of social media sites, social streams have proven to contain the most up-to-date information on current events. Therefore, it is crucial to extract events from the social streams such as tweets. However, it is not straightforward to adapt the existing event extraction systems since texts in social media are fragmented and noisy. In this paper we propose a simple and yet effective Bayesian model, called Latent Event Model (LEM), to extract structured representation of events from social media. LEM is fully unsupervised and does not require annotated data for training. We evaluate LEM on a Twitter corpus. Experimental results show that the proposed model achieves 83% in F-measure, and outperforms the state-of-the-art baseline by over 7%.© 2014 Association for Computational Linguistics.

Identifications with an ‘aesthetic’ and ‘moral’ diaspora amongst Tamils of diverse state origins in Britain

This chapter employs Pnina Werbner's notion of diasporas as moral communities of suffering and co-responsibility, as well as aesthetic communities of shared transnational consumption of culture and performance of ritual, and relates this to the case of Tamil migrants of diverse state origins in Britain. Sri Lankan Tamil migrants I interviewed towards my research imagine membership of a Tamil diaspora as based on personal (or familial) experiences of suffering in the Sri Lankan civil war, which acts both to create bonds with other Sri Lankan Tamils, and to distinguish from Tamils of other state origins (Indian, Singaporean etc.) despite cultural commonalities (Werbner's aesthetic diaspora). Conversely, many of the non-Sri Lankan Tamil migrants I interviewed imagined these boundaries in more flexible terms, and claimed membership of the 'community of suffering' in ways which did not necessitate personal experience, but rather privileged symbolic constructions of the ethnic community, and an interpretation of historical and current events in India, Sri Lanka (and other sites of Tamil population) as components of a single narrative of Tamil victimhood.

Stretching the life of Twitter classifiers with time-stamped semantic graphs

Social media has become an effective channel for communicating both trends and public opinion on current events. However the automatic topic classification of social media content pose various challenges. Topic classification is a common technique used for automatically capturing themes that emerge from social media streams. However, such techniques are sensitive to the evolution of topics when new event-dependent vocabularies start to emerge (e.g., Crimea becoming relevant to War Conflict during the Ukraine crisis in 2014). Therefore, traditional supervised classification methods which rely on labelled data could rapidly become outdated. In this paper we propose a novel transfer learning approach to address the classification task of new data when the only available labelled data belong to a previous epoch. This approach relies on the incorporation of knowledge from DBpedia graphs. Our findings show promising results in understanding how features age, and how semantic features can support the evolution of topic classifiers.

Premature cardiovascular events and mortality in south Asians with type 2 diabetes in the United Kingdom Asian Diabetes Study - effect of ethnicity on risk

Background/Aim - People of south Asian origin have an excessive risk of morbidity and mortality from cardiovascular disease. We examined the effect of ethnicity on known risk factors and analysed the risk of cardiovascular events and mortality in UK south Asian and white Europeans patients with type 2 diabetes over a 2 year period. Methods - A total of 1486 south Asian (SA) and 492 white European (WE) subjects with type 2 diabetes were recruited from 25 general practices in Coventry and Birmingham, UK. Baseline data included clinical history, anthropometry and measurements of traditional risk factors – blood pressure, total cholesterol, HbA1c. Multiple linear regression models were used to examine ethnicity differences in individual risk factors. Ten-year cardiovascular risk was estimated using the Framingham and UKPDS equations. All subjects were followed up for 2 years. Cardiovascular events (CVD) and mortality between the two groups were compared. Findings - Significant differences were noted in risk profiles between both groups. After adjustment for clustering and confounding a significant ethnicity effect remained only for higher HbA1c (0.50 [0.22 to 0.77]; P?=?0.0004) and lower HDL (-0.09 [-0.17 to -0.01]; P?=?0.0266). Baseline CVD history was predictive of CVD events during follow-up for SA (P?events in both groups and short period of follow-up are key limitations. Longer follow-up is required to see if the observed differences between the ethnic groups persist. Conclusion - South Asian patients with type 2 diabetes in the UK have a higher cardiovascular risk and present with cardiovascular events at a significantly younger age than white Europeans. Enhanced and ethnicity specific targets and effective treatments are needed if these inequalities are to be reduced.

Developing a conceptual framework for investigating the resilience of construction SMEs and their supply chains against extreme weather events

Projections into future increasingly suggest that the intensity and frequency of Extreme Weather Events (EWEs) will increase in the future. This has demanded the business organisations as well to be prepared to face the increasing risk of EWEs, in order to ensure their business continuity. However, current evidence base suggests that businesses, especially SMEs, are not adequately prepared to face the threat of such events. Ability to adequately prepare them has been hindered by the lack of in depth studies addressing this issue. The paper presents a doctoral study designed to investigate the resilience of SMEs operating in the construction sector; which is said to be a highly vulnerable sector for the impacts of EWEs, and their supply chains to EWEs. A conceptual framework developed to investigate this issue is presented and explained. It is argued that the resilience of construction SMEs and their supply chains against EWEs can be improved by a combination of reducing their vulnerability, enhancing coping capacity and implementing coping mechanisms. Importance of undertaking a broader view to include the whole supply chain in making business decisions with regard to EWEs by SMEs is also highlighted.

Coping strategies against extreme weather events:a survey of SMEs in the UK

Small and Medium-scale Enterprises (SMEs); which generate more than one half of the employment and turnover, form an important sector of the UK economy. In fact, SMEs are considered as the backbone of the UK economy due to their significant economic and societal importance. Despite SMEs being the main drivers of the UK economy, they are also said to be the most vulnerable to the impacts from various disruptions such as Extreme Weather Events (EWEs). Consequently, increased intensity and frequency of weather extremes in the UK during the recent past has created a significant impact on the SME community. As the threat of EWEs is expected to further increase in future, the need for SMEs to implement effective coping mechanisms to manage the effects of EWEs is also increasing. This paper aims to identify and evaluate the current coping mechanisms implemented by SMEs to ensure their business continuity in the event of a weather extreme. The paper presents the findings of a questionnaire survey, conducted as part of "Community Resilience to Extreme Weather - CREW" research project, addressing this issue. It is identified that SMEs mostly rely on generic business continuity strategies as opposed to property level protection measures. The paper highlights the importance of raising the uptake of coping strategies by SMEs, as many were found without adequate coping strategies to deal with the risk of EWEs.

Effects of extreme weather events on SMEs:a literature review and synthesis

Small and Medium-scale Enterprises (SMEs), which generate more than one half of the employment (58.9%) and turnover (51.9%), form an important sector of the UK economy. Although they are the main drivers of the UK economy, they are also said to be the most vulnerable to the impacts of Extreme Weather Events (EWEs). The world in recent years has experienced a significant number of EWEs, and SMEs have suffered significant economic losses as a result. The now apparent climate change, which is mostly attributed to human interference with the environment over the past few decades, is believed to have a strong link with the increase of EWEs in the recent past. Threats of EWEs are expected to further increase due to their increased frequency and magnitude and increased vulnerability to their effects. Interestingly, EWEs seem to present businesses with various business opportunities and positive consequences as well, besides the much feared and overwhelming threats and negative consequences they present. Understanding such impacts has become a necessity to improve the resilience of SMEs so that they will be better prepared to minimise the negative consequences and maximise the positive consequences posed by EWEs. This paper attempts to bring together and evaluate the current knowledge with regard to the effects of EWEs on SMEs. The paper establishes the case for more in-depth study with this regard and concludes by stressing the need for improving the resilience of SMEs to EWEs.