Social media could be thought as tools for disrupting prestige, position and geography based barriers for scientific conversations.
A few weeks ago, right before the mastodon wave, I summarized my takes on this in a tutorial for About Open on how to unleash the power of online tools for professional purposes in an open science environment.
Throughout the text I stressed the concept that every attempt to disseminate scientific outputs online is, above all, a scientific communication task. (1/3) 🧵
#openaccess #scicomm #altmetrics
Fine tune your content and target and carefully carve your threads for presenting your work online.
It takes time and committment to build and maintain an online professional reputation, no matter which is the platform you chose.
This is a possible way to transform the internet towards what was stated in the Berlin Declaration: a functional medium for distributing knowledge (3/3)🟨
@v_iacovella Not sure about "disrupting prestige". It also takes a lot of resources and (different) skills to do well in social media.
@OpenScienceFeed thanks for your comment.
I would agree with the second part (resources, skills, etc), even if I would say that you can keep it just informal / conversational and still dig out something from it. I would say that doing well on social media for scientific purposes have a different meaning wrt to the "standard" one (many followers, consistent interactions, etc).
Regarding the first part: I meant that it might be more likely to discuss with "big names" of a field online, where content - based conversations are basically open to everyone and in an asynchronous way, with respect to - for example - physical tables with restricted access in in - person conferences.
Real life interactions, among the other things, are a way to filter out scientific outputs, in order to avoid unnecessary reading and discover fresh, original ones. Tracing the impact of these interactions was possible only via citations, losing the trace of what brought authors to that mention.
DOIs and article level metrics are a way to quantitatively reconstruct a complete trace of impact. This applies to every published output! (2/3)