Your digital project is great, I’m sure of that – but does it even exist if nobody knows about it? Science communication is the answer to avoid this philosophical dilemma. In this short post, I wanted to share a list of quick-and-easy-to-implement ideas to add some science communication to your projects. This is just a short post to give you some ideas, not tutorials on how to do it. However, I am open to any tutorial requests you might have on the topics involved. As for the Twitter bot, there is a short post available already. So let’s get to it! Quick and easy strategies to #scicomm your DH project Create a better / thematic / facetted search interface. Maybe people aren’t using your data because the interface is not intuitive and they can’t find things or don’t know what to look for and where to look. This is the basic building block to build all the following things on.
This post wants to convince you to try out creating a Twitter bot using Python Tweepy and AmazonAWS Lambda because it’s easy and fun. Of course, you can use any other utilities but Tweepy and AWS Lambda are the ones I tried. This is not a full tutorial but I can make one if anyone is interested. Inspired by the #100DaysofDH challenge In this post, I will just give you some basic Twitter knowledge, links for what you need to know to get it done and a link to the github of my #100DaysofDH challenge for which I implemented such a bot. If you want more guidance, please let me know. Also, read the post on the challenge because I noted down some restrictions I realized the Twitter automation guidelines impose on bots as I went along. In my example, I think I’m in fact doing one or two things which you actually shouldn’t do (I think bots shouldn’t like