England vs. France, Messi, and Palestine are at the center of this week’s buzz on Twitter
Last week we looked at the top three FIFA players earning the most attention on Twitter. This week, the Media Insights Group (MIG) at Agility decided to delve into the larger topics creating buzz on Twitter.
Using a hybrid approach—combining machine learning with human review—the team analyzed the content of a sample of Tweets collected by Agility’s social listening solution that included the #FIFAWorldCup or #Qatar2022 hashtag. The analysis revealed six key categories and the percentage of the sample they represented:
Machine learning was used to identify topic clusters. These clusters were further reviewed for relevancy and accuracy by MIG—small clusters and outliers were removed to focus on more substantial groupings and some clusters were manually combined when there was obvious and substantial overlap. The result is the human-curated hierarchical topic presentation below:
The Match topic included tweets referencing the quarter final and last Round of 16 games. The England vs. France match in particular received a lot of buzz.
England lost to France 1-2 in the quarter finals. France is defending its 2018 title while England fans were hoping for England to take home the title for the first time since 1966. The posts analyzed were related pre-game predictions, sadness over the loss, and the criticized performance of referee Wilton Sampaio.
— Justin Smith (@Jbn024) December 10, 2022
“It’s coming home”
In 1996, two English comedians, David Baddiel and Frank Sinner, along with The Lightning Seeds, wrote a song to mark the return of the European Championship to the UK. The European Championship was the first major football tournament to be held in England since 1966 (the aforementioned World Cup). However, the song wasn’t enough to see England win in 1996 nor two years later when the song was re-released for the 1998 World Cup. Incidentally, both these games were lost due to missed penalty shots—a similar situation to what England found themselves in during the quarter finals match when Harry Kane missed his penalty shot, failing to level the score.
We looked at the top players on Twitter for last week’s coverage analysis, but unsurprisingly, Messi remained one of the top players this week too. Other players to get a lot of attention included Cristiano Ronaldo who is no longer in the tournament due to Portugal’s loss to Morocco in the quarter finals and England’s Harry Kane.
Messi’s “greatest of all time” or GOAT status was (and still is) being debated on Twitter. The question: can you be the GOAT without winning a World Cup?
You can’t be anywhere near the GOAT conversation until you’ve actually won the #FIFAWorldCup
It’s still Maradona and/or Pele https://t.co/3Jo9Tukjo9
— Joel Keane (@KeaneJoel) December 5, 2022
Out of the teams competing in the Round of 16 and the quarter finals, Morocco claimed the most buzz on Twitter.
Morocco is the first African country to qualify for the semifinals in a World Cup tournament. Tweets under the Morocco sub-category were qualified into four topics:
- The win against Spain
- Celebration (tweets had an element of personal investment)
- The recognition of its position as the first African country to make it to the semifinals
- Positive commendations for its performance in the tournament
The sub-topics under the “Other” category ranged from singer Jung Kook to human rights to gambling, but the two wave-making topics were Jung Kook and activist issues pertaining to Qatar’s human rights and Palestine.
Jung Kook, member of the popular South Korean band BTS, performed the song “Dreamer” at the opening ceremony of the World Cup. During the week of analysis, the song rose to the #7 spot on the United World Chart.
#Jungkook‘s #FIFAWorldCup song #Dreamers rockets 16-7 on the #UnitedWorldChart scoring 157k points in its 2nd week on the chart! #Dreamers was released on Nov 20 to coincide with the 1st match of this year’s World Cup & its opening ceremony, headlined by Jungkook!💪⚽️🎶🚀7⃣🌎👑💜 pic.twitter.com/HhZkEsVfFy
— World Music Awards (@WORLDMUSICAWARD) December 8, 2022
There were two main activist issues posted about on Twitter:
- Qatar’s human rights record which was one of the main themes discussed in our first week of FIFA coverage analysis
While not competing in the World Cup, Palestine has been dubbed the “33rd country” by some media due to its prominence during the tournament. Many players and fans have raised flags or worn armbands worn in support of the country. After the Round of 16 Morocco vs Spain match, Moroccan player Abdel Hamid Sabiri wore a Palestine flag.
— Atiqullah Hamza🇯🇴 (🎤ازاد خبریال) (@EmranHamza4) December 10, 2022
An opinion piece in Aljazeera said: “This year’s edition of the World Cup is the first one ever to be held in an Arab country. Hence, it has been more accessible – geographically, logistically and culturally – to people from the region than any previous World Cup. It has also given people from the region space to gather in large numbers without the usual fear of repression… As a result, Palestine has automatically taken centre stage, uniting Arabs in a joyful and celebratory atmosphere and reaffirming their commitment to the Palestinian cause.”
Not every post that used one of the hashtags was relevant. Opportunistic “trolls” piggy backed off the hashtags to get their tweets about cryptocurrencies and contests in front of as many eyes as possible.
The ultimate combo
Technology is great and Agility’s MIG will be the first to agree. But technology will only take you so far—the human touch is needed for proper refinement, relevancy, and curation. That’s why working with a team of media analysts who use cutting-edge analysis techniques combined with expert judgment will help you better understand the media landscape in your industry and for your brand. Interested in learning more? Contact us for your custom media monitoring and analysis needs!
Methodology and analysis
Using Agility’s social listening module, a sample of Tweets posted from December 5 to December 11 that included the hashtags #FIFAWorldCup or #Qatar2022 were analyzed. Only English tweets from accounts with at least 100 followers and with at least one interaction were included in the analysis.
Machine learning (BERTopic Python library) was used to identify topic clusters. BERTopic analyzed each tweet based on hundreds of dimensions to identify and cluster tweets based on latent similarities. MIG reviewed the results for relevancy and accuracy by removing small clusters and outliers and manually combining clusters where there was obvious and substantial overlap.