This project concerns a severe and critical situation. It is in no way meant to make fun of it, nor to take it lightly. On the contrary, it is meant to show how relevant and helpful digital approaches to anything human-related can be.

Our starting point is Russia-Ukraine Monitor Map by Cen4infoRes. Have a look at it, and start taking notes as to:

• what it is
• what it contains
• what it does not contain

We will first try to reproduce a rough version of the Russia-Ukraine Monitor Map by Cen4infoRes, based on data collected from Twitter. To achieve our goal, we will use the tools listed below. Read what they do, and have a look at their documentations to get a general understanding of how they can help us, and how we should interact with them (e.g. in which format should the data be passed to each tool?).

• twint
• snscrape
• OpenRefine | Documentation
• UMap | Documentation

Scraping Tweets by Location in Python using snscrape

These are available in the folder reports.

Digital Humanities UniMoRe 2022 The link with editor capabilities is shared on Teams!

Data is available in the data folder, and it currently contains the following:

• snscrape_since-20220316_random500.json collected on 22nd March 2022 using the command snscrape --jsonl --progress twitter-search "geocode:50.233152,36.166992,200km since:2022-03-16", it is a random sample of 500 tweets (i.e. JSON objects -> lines) from all the data collected during the scrape. The original file is too big to be included in this repo (240MB, while Github has a limit of 100MB per file), and you can find it in our Team shared folder