For what reasons do academics follow one another on Twitter? Robert Jäschke, Stephanie B. Linek and Christian P. Hoffmann analysed the Twitter activity of computer scientists and found that while the quality of information provided by a Twitter account is a key motive for following academic colleagues, there is also evidence of a career planning motive. As well as there being reciprocal following between users of the same academic status (except, remarkably, between PhD researchers), a form of strategic politeness can be observed whereby users follow those of higher academic status without necessarily being followed back. The emerging academic public sphere facilitated by Twitter is largely shaped by dynamics and hierarchies all too familiar to researchers struggling to plot their careers in academia.
Auf der Plattform handbuch.io des Open Science Lab der TIB Hannover schrieben vor und während der CeBIT 2014 in einem Book Sprint 15 eingeladene Expertinnen und Experten, viele davon aus dem Leibniz Forschungsverbund Science 2.0, das Handbuch CoScience - Gemeinsam forschen und publizieren mit dem Netz.
Auf der Plattform handbuch.io des Open Science Lab der TIB Hannover schrieben vor und während der CeBIT 2014 in einem Book Sprint 15 eingeladene Expertinnen und Experten, viele davon aus dem Leibniz Forschungsverbund Science 2.0, das Handbuch CoScience - Gemeinsam forschen und publizieren mit dem Netz.
Science 2.0 generally refers to new practices of scientists who post raw experimental results, nascent theories, claims of discovery and draft papers on the Web for others to see and comment on.
Proponents say these “open access” practices make scientific progress more collaborative and therefore more productive.
Critics say scientists who put preliminary findings online risk having others copy or exploit the work to gain credit or even patents.
Despite pros and cons, Science 2.0 sites are beginning to proliferate; one notable example is the OpenWetWare project started by biological engineers at the Massachusetts Institute of Technology.
Vast improvements in raw computing power, storage capacity, algorithms, and networking capabilities have led to fundamental scientific discoveries inspired by a new generation of computational models . . .Powerful 'data mining' techniques operating across