Discovering collective narratives shifts in online discussions

Narrative is a foundation of human cognition and decision making. Because narratives play a crucial role in societal discourses and spread of misinformation and because of the pervasive use of social media, the narrative dynamics on social media can have profound societal impact. Yet, systematic and computational understanding of online narratives faces critical challenge of the scale and dynamics; how can we reliably and automatically extract narratives from massive amount of texts? How do narratives emerge, spread, and die? Here, we propose a systematic narrative discovery framework that fill this gap by combining change point detection, semantic role labeling (SRL), and automatic aggregation of narrative fragments into narrative networks. We evaluate our model with synthetic and empirical data two-Twitter corpora about COVID-19 and 2017 French Election. Results demonstrate that our approach can recover major narrative shifts that correspond to the major events

Prediction and prevention of the next pandemic zoonosis.

Most pandemics--eg, HIV/AIDS, severe acute respiratory syndrome, pandemic influenza--originate in animals, are caused by viruses, and are driven to emerge by ecological, behavioural, or socioeconomic changes. Despite their substantial effects on global public health and growing understanding of the process by which they emerge, no pandemic has been predicted before infecting human beings. We review what is known about the pathogens that emerge, the hosts that they originate in, and the factors that drive their emergence. We discuss challenges to their control and new efforts to predict pandemics, target surveillance to the most crucial interfaces, and identify prevention strategies. New mathematical modelling, diagnostic, communications, and informatics technologies can identify and report hitherto unknown microbes in other species, and thus new risk assessment approaches are needed to identify microbes most likely to cause human disease. We lay out a series of research and surveillance opportunities and goals that could help to overcome these challenges and move the global pandemic strategy from response to pre-emption

Understanding Opportunities in Social Entrepreneurship: A Critical Realist Abstraction

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper extends social entrepreneurship (SE) research by drawing upon a critical realist perspective to analyse dynamic structure/agency relations in SE opportunity emergence, illustrated by empirical evidence. Our findings demonstrate an agential aspect (opportunity actualisation following a path-dependent seeding-growing-shaping process) and a structural aspect (institutional, cognitive and embedded structures necessary for SE opportunity emergence) related to SE opportunities. These structures provide three boundary conditions for SE agency: institutional discrimination, an SE belief system and social feasibility. Within this paper, we develop a novel theoretical framework to analyse SE opportunities plus, an applicable tool to advance related empirical research

‘Borne again in repetition’ : reincarnation, afterlives, and cultural memory in Amitav Ghosh’s The Calcutta Chromosome

The present article reads the social and cultural afterlives of a particular marginalised group in colonial Calcutta in Amitav Ghosh’s fourth novel The Calcutta Chromosome, and seeks to examine how these reconstructions of afterlives are linked with the ancient Indian philosophy of rebirth and reincarnation. This study seeks to understand the significance of body and ghost in reconstructing the afterlives and analyse the role of cultural memory throughout that process.peer-reviewe

The Role of Imagination in Social Scientific Discovery: Why Machine Discoverers Will Need Imagination Algorithms

When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from such activity? A close look at the methodology of interpretive social science reveals several abilities necessary to make a social scientific discovery, and one capacity necessary to possess any of them is imagination. For machines to make discoveries in social science, therefore, they must possess imagination algorithms

Human-Centric Cyber Social Computing Model for Hot-Event Detection and Propagation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Microblogging networks have gained popularity in recent years as a platform enabling expressions of human emotions, through which users can conveniently produce contents on public events, breaking news, and/or products. Subsequently, microblogging networks generate massive amounts of data that carry opinions and mass sentiment on various topics. Herein, microblogging is regarded as a useful platform for detecting and propagating new hot events. It is also a useful channel for identifying high-quality posts, popular topics, key interests, and high-influence users. The existence of noisy data in the traditional social media data streams enforces to focus on human-centric computing. This paper proposes a human-centric social computing (HCSC) model for hot-event detection and propagation in microblogging networks. In the proposed HCSC model, all posts and users are preprocessed through hypertext induced topic search (HITS) for determining high-quality subsets of the users, topics, and posts. Then, a latent Dirichlet allocation (LDA)-based multiprototype user topic detection method is used for identifying users with high influence in the network. Furthermore, an influence maximization is used for final determination of influential users based on the user subsets. Finally, the users mined by influence maximization process are generated as the influential user sets for specific topics. Experimental results prove the superiority of our HCSC model against similar models of hot-event detection and information propagation

Contextual Sensitivity in Grounded Theory: The Role of Pilot Studies

Grounded Theory is an established methodological approach for context specific inductive theory building. The grounded nature of the methodology refers to these specific contexts from which emergent propositions are drawn. Thus, any grounded theory study requires not only theoretical sensitivity, but also a good insight on how to design the research in the human activity systems to be studied. The lack of this insight may result in inefficient theoretical sampling or even erroneous purposeful sampling. These problems would not necessarily be critical, as it could be argued that through the elliptical process that characterizes grounded theory, remedial loops would always bring the researcher to the core of the theory. However, these elliptical remedial processes can take very long periods of time and result in catastrophic delays in research projects. As a strategy, this paper discusses, contrasts and compares the use of pilot studies in four different grounded theory projects. Each pilot brought different insights about the context, resulting in changes of focus, guidance to improve data collection instruments and informing theoretical sampling. Additionally, as all four projects were undertaken by researchers with little experience of inductive approaches in general and grounded theory in particular, the pilot studies also served the purpose of training in interviewing, relating to interviewees, memoing, constant comparison and coding. This last outcome of the pilot study was actually not planned initially, but revealed itself to be a crucial success factor in the running of the projects. The paper concludes with a theoretical proposition for the concept of contextual sensitivity and for the inclusion of the pilot study in grounded theory research designs

Astrobiology and Society in Europe Today

This book describes the state of astrobiology in Europe today and its relation to the European society at large. With contributions from authors in more than 20 countries and over 30 scientific institutions worldwide, the document illustrates the societal implications of astrobiology and the positive contribution that astrobiology can make to European society. The book has two main objectives: 1. It recommends the establishment of a European Astrobiology Institute (EAI) as an answer to a series of challenges relating to astrobiology but also European research, education, and society at large. 2. It also acknowledges the societal implications of astrobiology, and thus the role of the social sciences and humanities in optimizing the positive contribution that astrobiology can make to the lives of the people of Europe and the challenges they face