#SolidariTea, a twitter analysis

#SolidariTea was a worldwide event held in support for four female lecturers in NUI Galway (Ireland) who have been fighting gender discrimination in their experience at NUI Galway.

Supporters of the lecturers were asked to “Raise a cup of coffee or tea and tweet the hashtag #SolidariTea to show support” on the 8th of December 2017. The hashtag briefly trended within Ireland during the day, and was reported on by Irish Times.

I finally got around to performing some brief python analysis on the event through the use of extracting tweets which contained the #SolidariTea hashtag.

Disclaimer. Extracting tweets is a mildly complex process and is far from perfect. There’s a number of different methods available which have different advantages and disadvantages. The code I ended up forking gave us the advantage of pulling old tweets (which is harder than it sounds) but as a result we lost some information which would have been nice (Locations/usernames). It’s also a bit buggy..

Anyway, let’s get into the analysis!

I decided to export 800 tweets which contained the hashtag #SolidariTea. (800 seemed like the highest amount possible I could export in one go). This was reduced down to 191 unique tweets, by excluding re tweets. I ran a quick check to see that no tweet was posted outside of the range of 6th–7th–8th of December.

We start by dividing each tweet into which hour it was posted (10.00 o’clock, 11.00 o’clock etc etc). We plot this on the graph to see a frequency distribution.

It make sense to see that mid-morning, 11am and 12am where the most popular times with the 16.00 hour coffee slump and dinner time being popular as well.

But wait! Why is there tweets so early in the morning and so late at night? 🤔. That’s because when I exported the tweets twitter automatically set all times to reference off my timezone (GMT+1). So those tweets were probably sent at reasonable times but in different time zones such as GMT-6 or +6.

Moving on anyway, let’s look at how popular #SolidariTea was.

Tweets that contained #SolidariTea:
Total re-tweets: 961
Total favorites: 2684

Those stats are pretty good I’d have to say, but we can dig a little deeper!

Re-tweets verse Favorites

Here’s a plot of re-tweets versus favourites. As is expected, we see a rough linear trend (tweets often have a equal number of favourites and re-tweets) which makes sense. However, we see something kind of odd, a single tweet with 67 favorites and 31 re-tweets….?

This is a bit of a mystery 👻, so I was able to find this text in our dataset.

Text         virtual herbal tea from me in support of #soli...
mentions      @ucddublin @nuigalway @NUIGsolidariTEA @CGFS_UCD
retweets                                                    31
hastags                                           #solidaritea
date                                       2017-12-07 23:21:08
geo                                                           
favorites                                                   67

Next I went looking for it in Twitter, using tTwitter’s advanced search feature. I tried a number of different search terms, and I couldn’t find the tweet, which seems odd since if it was really that popular?

I decided that it was probably a mistake with the code I used to export tweets, as I mentioned before it’s not a prefect script and I assume it messed up in this case.

Let’s put that aside, and try one or two final things.

When you “@” someone on twitter, it’s called a mention. I wrote some code which extracted every mentions from a tweet and sorted them.

@NUIGsolidariTEA    95
@nuigalway          39
@kellycoate          6
@FemSocNUIG          5
@MichelineShSk       5
@aliceeire           4
@Afshin_Samali       4
@ivanabacik          3
@folieadeuxed        3
@gcs_ul              3
@NUIGSU              3
@stritchj            3
@AppSocScs_LIT       3
@CGFS_UCD            3
@lisascottpsych      3
@NUIGLaw             2
@ucddublin           2

I found the following list of top mentions.

I was able to do the same for hashtags.

#solidariTEA             168
#SolidariTEA              15
#genderdiscrimination     13
#genderequality            8
#NUIG                      4
#solidariTea               4
#solidaritea               3
#HE                        2
#kingscollegelondon        2
#Solidaridad               2
#genderstudies             1
#HigherEducation           1
#AlcaladeHenares           1
#Navidad                   1
#solidarity                1
#feminism                  1
#sspp                      1
#Alcala                    1
#Oireachtas                1
#impact                    1
#Cardiff                   1
#womeninhighered           1
#WomenInAcademia           1

I’m not even sure what some of those hashtags mean… and why someone would be tweeting about SPSS..😨

Finally, I did the same for words in each tweet. I removed stop words (in, to, and etc) and came up with this list.

#solidariTEA                  168
support                        54
@nuigalway                     39
colleagues                     32
gender                         30
our                            26
cup                            23
women                          22
discrimination                 19
morning                        15
coffee                         15
equality                       14

Conclusion:

All of this is the most basic level of twitter analysis possible, I didn’t do anything cool like sentiment analysis or location cross-reference.

I’ve made all my work public, along with the dataset. You’re more than welcome to review my work and critique it in the interest of good science or download the dataset and perform your own analysis!

Any questions just comment below, and be sure to give me a clap 👏 if you liked this!