37 resultados para Social media analysis and engagement
Resumo:
This paper provides a summary of the Social Media and Linked Data for Emergency Response (SMILE) workshop, co-located with the Extended Semantic Web Conference, at Montpellier, France, 2013. Following paper presentations and question answering sessions, an extensive discussion and roadmapping session was organised which involved the workshop chairs and attendees. Three main topics guided the discussion - challenges, opportunities and showstoppers. In this paper, we present our roadmap towards effectively exploiting social media and semantic web techniques for emergency response and crisis management.
Resumo:
The public’s perception of the social work profession is a rarely considered perspective, and yet a topic that is a concern to front Thepublic’sperceptionofthesocialworkprofessionisararelyconsideredperspective and yet a topic that is a concern to front line professionals. This paper explores how social workers experience and attempt to cope with public perception of their profession. It highlights the impact of these concerns on social workers’ personal experiences and professional practice. Using semi-structured interviews with sixteen UK social workers, from local authorities and private organisations,we explore the experiences of this group.Thematic analysis of the data identified four concerns: the experience of public perception, drivers of public perception, coping with public perception, and mechanisms to raise the professions profile. Examining public perception through the eyes of social workers provides valuable insights into the lived experiences of these professionals, and offers practical implications at both the micro and macro levels. It reveals two key ways in which the profession can begin to address the prevailing negative perception considered to be emanating from the public: through developing a more co-operative relationship with external sources of public perception (e.g. government and the media) and by engaging in more pro-active self-promotion of the service.
Resumo:
This cross-country report shares first insights from the World's Largest Panel Study of Social Enterprises, which covers seven European Countries (Germany, Hungary, Portugal, Romania, Spain, Sweden, the United Kingdom), China and Russia. It captures the behavior and characteristics of representative samples of social enterprises in these countries who are employers. The report covers a range of topics from profiling social enterprise directors and their social enterprises, to innovation activities and barriers, their entrepreneurial orientation, social missions, social impact metrics to summarizing policy recommendations that social entrepreneurs would like to see being implemented in their countries. Who should read this report? The report is written for social enterprises, social enterprises support organisations and policy makers who want to get an overview of social enterprise in the UK. Thank you to all the social entrepreneurs who made this report possible by participating in our study!
Resumo:
A participant observation method was employed :in the study of a 20-week stoppage at Ansells Brewery Limited, a constituent company of Allied Breweries (U.K.). The strike, :involving 1,000 workers, began :in opposition to the implementation of a four-day working week and culminated in the permanent closure of the brewery. The three main phases of the strike's development (i.e., its :initiation, maintenance and termination) were analysed according to a social-cognitive approach, based on the psychological imagery, beliefs, values and perceptions underlying the employees' behaviour. Previous psychological treatments of strikes have tended to ignore many of the aspects of social definition, planning and coordination that are an integral part of industrial action. The present study is, therefore, unique in concentrating on the thought processes by which striking workers .make sense of their current situation and collectively formulate an appropriate response. The Ansells strike provides an especially vivid illustration of the ways in which the seminal insights of a small number of individuals are developed, via processes of communication and:influence, into a consensual interpretation of reality. By adopting a historical perspective, it has been possible to demonstrate how contemporary definitions are shaped by the prior history of union-management relations, particularly with regard to: (a) the way that previous events were subjectively interpreted, and (b) the lessons that were learned on the basis of that experience. The present approach is psychological insofar as it deals with the cognitive elements of strike action. However, to the extent that it draws from relevant sections of the industrial relations, organizational behaviour, sociology, anthropology and linguistics literatures, it can claim to be truly interdisciplinary.
Resumo:
Background The role of applied theatre in engaging both lay and professional publics with debate on health policy and practice is an emergent field. This paper discusses the development, production performance and discussion of ‘Inside View’.1 Objectives The objectives were to produce applied theatre from research findings of a completed study on genetic prenatal screening, exploring the dilemmas for women and health professionals of prenatal genetic screening, and to engage audiences in debate and reflection on the dilemmas of prenatal genetic screening. Methods ‘Inside View’ was developed from a multidisciplinary research study through identification of emergent themes from qualitative interviews, and development of these by the writer, theatre producer and media technologist with input from the researchers. Findings Inside View was performed in London and the Midlands to varied audiences with a panel discussion and evaluation post performance. The audiences were engaged in debate that was relevant to them professionally and personally. Knowledge translation through applied theatre is an effective tool for engaging the public but the impact subsequently is unclear. There are ethical issues of unexpected disclosure during discussion post performance and the process of transforming research findings into applied theatre requires time and trust within the multidisciplinary team as well as adequate resourcing.
Resumo:
In this poster we presented our preliminary work on the study of spammer detection and analysis with 50 active honeypot profiles implemented on Weibo.com and QQ.com microblogging networks. We picked out spammers from legitimate users by manually checking every captured user's microblogs content. We built a spammer dataset for each social network community using these spammer accounts and a legitimate user dataset as well. We analyzed several features of the two user classes and made a comparison on these features, which were found to be useful to distinguish spammers from legitimate users. The followings are several initial observations from our analysis on the features of spammers captured on Weibo.com and QQ.com. ¦The following/follower ratio of spammers is usually higher than legitimate users. They tend to follow a large amount of users in order to gain popularity but always have relatively few followers. ¦There exists a big gap between the average numbers of microblogs posted per day from these two classes. On Weibo.com, spammers post quite a lot microblogs every day, which is much more than legitimate users do; while on QQ.com spammers post far less microblogs than legitimate users. This is mainly due to the different strategies taken by spammers on these two platforms. ¦More spammers choose a cautious spam posting pattern. They mix spam microblogs with ordinary ones so that they can avoid the anti-spam mechanisms taken by the service providers. ¦Aggressive spammers are more likely to be detected so they tend to have a shorter life while cautious spammers can live much longer and have a deeper influence on the network. The latter kind of spammers may become the trend of social network spammer. © 2012 IEEE.
Resumo:
In this study, we examined the associations of personality traits of the Big Five model with work engagement, and tested a theoretical model in which these associations are mediated by the positive state of psychological meaningfulness (perceptions that work is valuable and meaningful). In a sample of 238 UK working adults, we found that the personality facets assertiveness and industriousness were the strongest predictors of work engagement, and that both exhibited direct and indirect effects, mediated by psychological meaningfulness. Neuroticism demonstrated a marginal indirect association with engagement, again mediated by psychological meaningfulness. Our findings offered good support for our model, explaining a pathway from personality traits to engagement. Practical implications for management are discussed. © 2013 Wiley Periodicals, Inc.
Resumo:
Social streams have proven to be the mostup-to-date and inclusive information on cur-rent events. In this paper we propose a novelprobabilistic modelling framework, called violence detection model (VDM), which enables the identification of text containing violent content and extraction of violence-related topics over social media data. The proposed VDM model does not require any labeled corpora for training, instead, it only needs the in-corporation of word prior knowledge which captures whether a word indicates violence or not. We propose a novel approach of deriving word prior knowledge using the relative entropy measurement of words based on the in-tuition that low entropy words are indicative of semantically coherent topics and therefore more informative, while high entropy words indicates words whose usage is more topical diverse and therefore less informative. Our proposed VDM model has been evaluated on the TREC Microblog 2011 dataset to identify topics related to violence. Experimental results show that deriving word priors using our proposed relative entropy method is more effective than the widely-used information gain method. Moreover, VDM gives higher violence classification results and produces more coherent violence-related topics compared toa few competitive baselines.
Resumo:
Social Media is becoming an increasingly important part of people’s lives and is being used increasingly in the food and agriculture sector. This paper considers the extent to which each section of the food supply chain is represented in Twitter and use the hashtag #food. We looked at the 20 most popular words for each part of the supply chain by categorising 5000 randomly selected tweets to different sections of the food chain and then analysing each category. We sorted the users by those who tweeted most frequently and categorised their position in the food supply chain. Finally to consider the indegree of influence, we took the top 100 tweeters from the previous list and consider what following these users have. From this we found that consumers are the most represented area of the food chain, and logistics is the least represented. Consumers had 51.50% of the users and 87.42% of the top words tweeted from that part of the food chain. We found little evidence of logistics representation for either tweets or users (0.84% and 0.35% respectively). The top users were found to follow a high percentage of their own followers with most having over 70% the same. This research will bring greater understanding of how people perceive the food sector and how Twitter can be used within this sector.
Resumo:
Neuroimaging (NI) technologies are having increasing impact in the study of complex cognitive and social processes. In this emerging field of social cognitive neuroscience, a central goal should be to increase the understanding of the interaction between the neurobiology of the individual and the environment in which humans develop and function. The study of sex/gender is often a focus for NI research, and may be motivated by a desire to better understand general developmental principles, mental health problems that show female-male disparities, and gendered differences in society. In order to ensure the maximum possible contribution of NI research to these goals, we draw attention to four key principles—overlap, mosaicism, contingency and entanglement—that have emerged from sex/gender research and that should inform NI research design, analysis and interpretation. We discuss the implications of these principles in the form of constructive guidelines and suggestions for researchers, editors, reviewers and science communicators.
Resumo:
This paper contributes to the recent ‘practice turn’ in management accounting literature in two ways: (1) by investigating the meshing and consequently the ‘situated functionality’ of accounting in various private equity (PE) practices, and (2) by experimenting with the application of Schatzki’s ‘site’ ontology. By identifying and describing the role and nature of accounting and associated calculative practices in different parts of the PE value chain, we note that the ‘situated functionality’ of accounting is ‘prefigured’ by its ‘dispersed’ nature. A particular contribution of experimenting with Schatzki’s ‘site’ ontology has been to identify theoretical concerns in relation to the meaning and role of the concept ‘general understandings’ and to clarify the definitional issues surrounding this concept. We also identify the close relationship between ‘general understandings’ and ‘teleoaffective structure’ and note their mutually constitutive nature.
Resumo:
This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.
Resumo:
Topic classification (TC) of short text messages offers an effective and fast way to reveal events happening around the world ranging from those related to Disaster (e.g. Sandy hurricane) to those related to Violence (e.g. Egypt revolution). Previous approaches to TC have mostly focused on exploiting individual knowledge sources (KS) (e.g. DBpedia or Freebase) without considering the graph structures that surround concepts present in KSs when detecting the topics of Tweets. In this paper we introduce a novel approach for harnessing such graph structures from multiple linked KSs, by: (i) building a conceptual representation of the KSs, (ii) leveraging contextual information about concepts by exploiting semantic concept graphs, and (iii) providing a principled way for the combination of KSs. Experiments evaluating our TC classifier in the context of Violence detection (VD) and Emergency Responses (ER) show promising results that significantly outperform various baseline models including an approach using a single KS without linked data and an approach using only Tweets. Copyright 2013 ACM.