🇪🇺 #EuropeanSuperLeague

Using my #data analysis tools, I tried to measure what role Twitter played in this failure:

Without this network, would the closed league project, led by the 12 richest clubs in Europe, have had the same fate?

[THREAD] ⤵️
To analyze what happened and answer this question, I extracted a large amount of data:

2.6 million tweets posted by 876,000 unique users
5 targeted languages : 🇫🇷 🇬🇧 🇪🇦 🇮🇹 🇩🇪
56 million likes and 7.8 million retweets
The tweets collected start from April 17th at noon to April 22nd at midnight.

I'm going to go back over the facts chronologically so that we can relive this story from the Twitter standpoint.

First of all, here is the distribution of the tweets I collected on the period:
It all starts on April 18th, at 3pm:

It's a Sunday afternoon and @tariqpanja, a reporter from the New York Times, publishes an article that will be like a bombshell:
This article explains that the 12 richest football clubs in Europe will announce the creation of a closed league, where performance will no longer matter to qualify.
This information is relayed and confirmed by important actors in different countries (like @mohamedbouhafsi in France or @danroan in England) so it begins : Twitter starts to ignite

But the real fire will start in the middle of the night:
Around midnight, the 12 clubs that have been working in secret will officially and simultaneously announce the creation of this closed league, through press releases relayed on their official pages.

Here, I sampled my dataset to focus on the reactions of English and Spanish users to the announcement of the creation of the super league.

To perform sentiment analysis, I mapped the emojis used in these tweets:
What I find interesting here is to analyze the differences between these maps to detect low signals.
Thus, we can see that although the general feeling is similar (laughter, amusement), the secondary feelings are different between Spanish and English users.
When we zoom on the English side, the vast majority of emojis that stand out represent bad feelings: 🤬💔🤮...

A few supportive emojis are present, but they are a very minority.
On the Spanish side, the secondary feelings are much more divided!

We obvously find negative emojis on one side, but also a large amount of enthusiastic emojis: 🤩😍😎...
The presence of hearts, in the colors of the real and barça, supports this feeling: ❤️💙🤍
To go further in this sentiment analysis, I also analyzed the semantics of the answers to the press releases of the announcement of the Super League.
As for the #UCL semi-final, we will focus on the publications of Real and Chelsea:
On the Real side, we can detect 4 semantic communities corresponding to different languages:

🟠 Orange: Spanish
🔴 Red: English
🔵 Blue: French
🟢 Green: Portuguese

The three non-Spanish speech fields are unanimously pejorative.
When focusing on the Spanish discourse, we notice two distinct semantic fields: a very negative one (in red) that attacks the decision of the real and a very general one (in green).
The insults and attacks are obvious, but once again, it's the comparison that's interesting.

In the semantic cartography from the answers to Chelsea's posts (below), we see that the negative part is much more important!
Now let's get back to our story.
The two days following the announcement were very eventful on Twitter, especially after speeches of some players, coaches or public figures...

Here is a representation of the mentions of the English clubs involved, cumulated over the period.

We can see that there has been a constant pressure on the involved Premier League clubs.
And then suddenly, the edifice cracks:

On Tuesday, April 20, at 8 p.m., less than two days after the official announcement of the Super League, the English press announced that Chelsea wanted to withdraw from the project!
We quickly learn that all English clubs want to abandon the closed league project!

The same night, around midnight, it is official: the six Premier League clubs involved post their declaration of rupture and thus stop the project.
I've sampled my corpus of tweets to perform the same sentiment analysis and semantic mapping process that before.

My goal is to use the first analysis as a reference to study the emotional differential on the withdrawal announcement.
The emoji mappings brings out the same main feeling: mockery.
The ridiculousness of the situation, of such a colossal project collapsing in two days, comes across 😂🤡🥶...
Joy is the second most represented sentiment, with celebrations and supportive emojis 🥳👏💪...
However, what is very interesting is the presence of a large network of disappointed and reluctant emojis on the Spanish mapping.
On the contrary, these emojis (such as 😔) are negligible on the English mapping.
This analysis is in harmony with various polls, which showed that the Spanish fans were the most enthusiastic about the idea of a closed league.
lequipe.fr/Football/Actua…
Finally, to bring things full circle, when we take a look at the semantics used in the responses to Chelsea's withdrawal post, we get the following mapping:
Insults and shame have been replaced by thanks and very positive statements.

But beware, the fans are not fooled and an important semantic field corresponds to demands of apology from the leaders!
Of course, even after this analysis, it would be an exaggeration to say that it is mainly thanks to Twitter that this project fell through: in parallel to this virtual popular vindication, many other factors came into play.
Fans went to the streets, other clubs united against the super league, uefa and fifa exerted strong pressure, the British Prime Minister @BorisJohnson even threatened to put a "legislative bomb" in place to make this project impossible!
I still think that what may have been the driving force behind this union against the super league was this pressure from the supporters online.
We can easily imagine that if supporters had supported this reform, many public actors would not have committed themselves against it.
Moreover, the sanitary context is also very important: in this period of restrictions, the stadiums are empty and the streets deserted.
To communicate with each other and bring messages, social networks have become a fundamental channel that allows to keep the link between people and to create real virtual strikes like this.
I still have a lot of insights on this topic, and I'll come back on the afternoon with a complementary thread on the question: in this kind of crisis, who are the football key opinion leaders on Twitter in Europe?

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More from @nicolasbchb

7 May
🇪🇺 Key Opinion leaders ⚽

Recently, the failed #EuropeanSuperLeague project set #Twitter on fire.

Between the millions of tweets published on the subject, some voices had a particularly important weight.

Here are the #KOL of European football according to #data:

[THREAD]⤵️
This thread is the continuation of the analysis I shared on the impact of Twitter on the Super League collapse.

The #dataset used is the same: 2.6 million tweets posted by 876,000 unique users in 5 languages (🇬🇧 🇫🇷 🇪🇦 🇮🇹 🇩🇪 )

In my first analysis, I focused on the contents (sentiment analysis, semantic cartographies...), here the goal is to analyze the influential content providers in Europe.
Read 24 tweets
5 May
🇪🇺 Leaders d'opinion ⚽

Récemment, le projet avorté #EuropeanSuperLeague a fait s'enflammer #Twitter.

Au cœur des millions de tweets publiés sur le sujet, des voix ont un poids particulièrement important.

Voici les #KOL du foot européen selon la #data :

[THREAD] ⤵️
Ce thread est la suite de l'analyse que j'avais partagé sur l'impact de Twitter dans l'abandon de la Super League.

Le #dataset utilisé est le même : 2,6 millions de tweets postés par 876 000 users uniques dans 5 langues (🇫🇷 🇬🇧 🇪🇦 🇮🇹 🇩🇪 )

Là où dans la première analyse je me consacrais sur les contenus (sentiment analysis, cartographies sémantiques...), ici l'objectif est d'analyser les émetteurs de contenu influents.
Read 25 tweets
30 Apr
🇪🇺 #EuropeanSuperLeague

En utilisant mes outils de #DataScience, j'ai essayé de mesurer quel rôle a joué #Twitter dans cet échec :

Sans ce réseau, le projet de ligue fermée mené par les 12 clubs les plus riches d'Europe aurait-il vécu le même sort ?

[THREAD] ⤵️
Pour analyser ce qu'il s'est passé et répondre à ma question, j'ai extrait une grande quantité de données :

2,6 millions de tweets postés par 876 000 users uniques
5 langues ciblées : 🇫🇷 🇬🇧 🇪🇦 🇮🇹 🇩🇪
56 millions de likes et 7,8 millions de retweets cumulés Image
Les tweets récoltés vont du 17 avril midi, jusqu'au 22 avril minuit.

Je vais revenir sur les faits chronologiquement pour qu'on revive cette histoire en suivant l'angle Twitter.

Voici tout d'abord la répartition des tweets que j'ai récupéré sur la période : Image
Read 34 tweets

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