At this past week’s Archives Unleashed dataton, I jokingly created some wordclouds of my Co-PI’s timelines.
Finished my most likely bigly winning #hackarchives project: A Word Cloud of @lintool's timeline!https://t.co/eK2KPGjaGo
— nick ruest (@ruebot) April 27, 2018
Or, @ianmilligan1 #HackArchiveshttps://t.co/qMxiet0osl
— nick ruest (@ruebot) April 27, 2018
Mat Kelly asked about the process this morning, so here is a little how-to of the pipeline:
twarc jq wordcloud_cli.
Tweets to Donald Trump (@realDonaldTrump) 59,261,490 tweet ids for tweets directed at Donald Trump (@realDonaldTrump), collected with Documenting the Now's twarc. Tweets can be “rehydrated” with Documenting the Now’s twarc, or Hydrator.
twarc hydrate to_realdonaldtrump_ids.txt to_donaltrump.jsonl. Tweets from May 7, 2017 - June 21, 2017 of the dataset used a combination of the Filter (Streaming) API and Search API. The Filter API failed on June 21, 2017. From June 23, 2017 forward only the Search API was used to collect.
Overview A couple Saturday mornings ago, I was on the couch listening to records and reading a book when Christina Harlow and MJ Suhonos asked me about collecting #WomensMarch tweets. Little did I know at the time #WomensMarch would be the largest volume collection I have ever seen. By the time I stopped collecting a week later, we’d amassed 14,478,518 unique tweet ids from 3,582,495 unique users, and at one point hit around 1 million tweets in a single hour.
On November 13, 2015 I was at the “Web Archives 2015: Capture, Curate, Analyze” listening to Ian Milligan give the closing keynote when Thomas Padilla tweeted the following to me:
@ruebot terrible news, possible charlie hebdo connection - https://t.co/SkEusgqgz5
— Thomas Padilla (@thomasgpadilla) November 13, 2015
I immediately started collecting.
When tragedies like this happen, I feel pretty powerless. But, I figure if I can collect something like this, similar to what I did for the Charlie Hebdo attacks, it’s something.
#JeSuisCharlie #JeSuisAhmed #JeSuisJuif #CharlieHebdo I’ve spent the better part of a month collecting tweets from the #JeSuisCharlie, #JeSuisAhmed, #JeSuisJuif, and #CharlieHebdo tweets. Last week, I pulled together all of the collection files, did some clean up, and some more analysis on the data set (76G of json!). This time I was able to take advantage of Peter Binkley’s twarc-report project. According to the report, the earliest tweet in the data set is from 2015-01-07 11:59:12 UTC, and the last tweet in the data set is from 2015-01-28 18:15:35 UTC.
#JeSuisAhmed Had some time last night to do some exploratory analysis on some of the #JeSuisAhmed collection. This analysis is from the first tweet I was able to harvest #JeSuisAhmed to some time on January 14, 2015 when I copied over the json to experiment with a few of the twarc utilities.
First tweet in data set:
#JeSuisAhmed Reveals the Hero of the Paris Shooting Everyone Needs to Know by @sophie_kleeman http://t.
Using the #JeSuisCharlie data set from January 11, 2015 (Warning! Will turn your browser into a potato for a few seconds), these are the image urls that have more than 1000 occurrences in the data set.
How to create (requires unshrtn):
% twarc.py --query "#JeSuisCharlie" % ~/git/twarc/utils/deduplicate.py JeSuisCharlie-tweets.json > JeSuisCharlie-tweets-deduped.json % cat JeSuisCharlie-tweets-deduped.json | utils/unshorten.py > JeSuisCharlie-tweets-deduped-ushortened.json % ~/git/twarc/utils/image_urls.py JeSuisCharlie-tweets-deduped-ushortened.json >| JeSuisCharlie-20150115-image-urls.txt % cat JeSuisCharlie-20150115-image-urls.txt | sort | uniq -c | sort -rn > JeSuisCharlie-20150115-image-urls-ranked.
Background Last Friday (January 9, 2015) I started capturing #JeSuisAhmed, #JeSuisCharlie, #JeSuisJuif, and #CharlieHebdo with Ed Summers’ twarc. I have about 12 million tweets at the time of writing this, and plan on writing up something a little bit more in-depth in the coming weeks. But for now, some preliminary analysis of #JeSuisCharlie, and if you haven’t seen these two posts (”A Ferguson Twitter Archive”, “On Forgetting and hydration”) by Ed Summers, please do check them out.
Another example of how global the Rob Ford scandal has become via harvested tweets with geographic coordinates. This example is a harvest of #rofo, #robford, #topoli, and #ShirtlessHorde.
The harvest took place on July 6, 2014, and should cover the discussion around the time of Rob Ford's return on June 30, 2014 to July 6, 2014. The tweets with available geo-information represents less than 10% of all tweets harvested.