Using TAGS
During our last Digital Information Technologies and Architectures (DITA) class, we were introduced to searching and archiving tweets using the TAGS (Twitter Archiving Google Sheet) application developed by Martin Hawksey.
This app is a mashup that uses the Twitter Search API and Google Sheets API to enable users to easily search, collect and archive tweets containing a specific term or hashtag from the past seven days. Along with the tweets themselves, TAGS also collects and archives the metadata related to each tweet, including the time and date when a tweet was sent, the username of the person sending the tweet, the number following and number of followers, and whether a tweet was sent in response to another tweet.
In addition to providing a spreadsheet listing this information, TAGS also provides a summary of the tweets and some visualisations of the tweets collected.
#melbourneweather
Following on from the Melbourne weather theme of my last post, this week I used TAGS to search, archive and analyse tweets containing #melbourneweather for the fortnight from Monday 20 October until Sunday 2 November. An initial glance glance at the output from TAGS showed a huge spike in the number of tweets with this hashtag on Monday 27 October, with 622 tweets sent that day, compared with an average of just 18 tweets per day the week before.
So why were there so many tweets about the weather on that day? A quick search uncovered that there had been a huge storm early on Monday morning in Melbourne which caused flash-flooding and the most rain for a year. The storm caused major disruptions to public transport caused several flights to be delayed and left many without electricity.
The following graph shows the daily amount of rainfall along with the number of tweets tagged with #melbourneweather. This shows – as is probably bleedingly obvious – that there is a link between the weather events, and the use of this hashtag.
Drinking from the fire hose 