Dataset Information

The Topology of a Discussion: The #Occupy Case.

ABSTRACT: We analyse a large sample of the Twitter activity that developed around the social movement 'Occupy Wall Street', to study the complex interactions between the human communication activity and the semantic content of a debate.We use a network approach based on the analysis of the bipartite graph @Users-#Hashtags and of its projections: the 'semantic network', whose nodes are hashtags, and the 'users interest network', whose nodes are users. In the first instance, we find out that discussion topics (#hashtags) present a high structural heterogeneity, with a relevant role played by the semantic hubs that are responsible to guarantee the continuity of the debate. In the users' case, the self-organisation process of users' activity, leads to the emergence of two classes of communicators: the 'professionals' and the 'amateurs'.Both the networks present a strong community structure, based on the differentiation of the semantic topics, and a high level of structural robustness when certain sets of topics are censored and/or accounts are removed.By analysing the characteristics of the dynamical networks we can distinguish three phases of the discussion about the movement. Each phase corresponds to a specific moment of the movement: from declaration of intent, organisation and development and the final phase of political reactions. Each phase is characterised by the presence of prototypical #hashtags in the discussion.

SUBMITTER: Gargiulo F

PROVIDER: S-EPMC4564107 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Topology of a Discussion: The #Occupy Case.

Gargiulo Floriana F Bindi Jacopo J Apolloni Andrea A

PloS one 20150909 9

<h4>Introduction</h4>We analyse a large sample of the Twitter activity that developed around the social movement 'Occupy Wall Street', to study the complex interactions between the human communication activity and the semantic content of a debate.<h4>Methods</h4>We use a network approach based on the analysis of the bipartite graph @Users-#Hashtags and of its projections: the 'semantic network', whose nodes are hashtags, and the 'users interest network', whose nodes are users. In the first insta ...[more]

PMID: 26352596

Similar Datasets

Project description:ObjectiveTo explore the issue of counterintuitive data via analysis of a representative case in which the data obtained was unexpected and inconsistent with current knowledge. We then discuss the issue of counterintuitive data while developing a framework for approaching such findings.DesignThe case study is a retrospective analysis of a cohort of coronary artery bypass graft (CABG) patients. Regression was used to examine the association between perceived pain in the intensive care unit (ICU) and selected outcomes.SettingMedical Information Mart for Intensive Care-III, a publicly available, de-identified critical care patient database.Participants844 adult patients from the database who underwent CABG surgery and were extubated within 24 hours after ICU admission.Outcomes30 day mortality, 1 year mortality and hospital length of stay (LOS).ResultsIncreased pain levels were found to be significantly associated with reduced mortality at 30 days and 1 year, and shorter hospital LOS. A one-point increase in mean pain level was found to be associated with a reduction in the odds of 30 day and 1 year mortality by a factor of 0.457 (95% CI 0.304 to 0.687, p<0.01) and 0.710 (95% CI 0.571 to 0.881, p<0.01) respectively, and a 0.916 (95% CI -1.159 to -0.673, p<0.01) day decrease in hospital LOS.ConclusionThe finding of an association between increased pain and improved outcomes was unexpected and clinically counterintuitive. In an increasingly digitised age of medical big data, such results are likely to become more common. The reliability of such counterintuitive results must be carefully examined. We suggest several issues to consider in this analytic process. If the data is determined to be valid, consideration must then be made towards alternative explanations for the counterintuitive results observed. Such results may in fact indicate that current clinical knowledge is incomplete or not have been firmly based on empirical evidence and function to inspire further research into the factors involved.

Dataset Information

The Topology of a Discussion: The #Occupy Case.

Publications

The Topology of a Discussion: The #Occupy Case.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure