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Survey reveals which Hammers send stress levels racing


Filed: Friday, 12th July 2019
By: Staff Writer


Analysis of tweets by West Ham fans on Premier League derby days over the last two seasons reveal that Pedro Obiang was the most stressful West Ham player.

No less than 93 in every 1,000 Hammers fans tweeted anxiously about the player during London derbies during the 2017/18 and 2018/19 campaigns - whilst Mark Noble, Declan Rice, Andy Carroll and Felipe Anderson also received a significant number of mentions.

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Analysts Casumo evaluated some 400,000 tweets - using a tool called TensiStrength - to find out the highest proportion of stressed-out fans before, during and after the Premier League’s biggest local rivalries.

And results revealed that Obiang was the most stressful player for Hammers fans overall - whilst the top five Hammers to receive mentions were as follows:

1. Pedro Obiang: 93 (mentions per 1000 tweets)
2. Mark Noble: 15
3. Declan Rice: 13
4. Andy Carroll: 12
5. Felipe Anderson: 10

Not only was Obiang the subject of most stressed posts by West Ham fans, but he also topped a list of the top ten players most referenced by supporters across the entire Premier League:

1. Pedro Obiang: 93 (mentions per 1000 tweets)
2. Eden Hazard: 62
3. Harry Kane: 45
4. Romelu Lukaku: 40
5. Riyad Mahrez: 39
6. Mohamed Salah: 34
7. Marcos Alonso: 33
8. Pierre-Emerick Aubameyang: 33
9. Paul Pogba: 33
10. Moussa Sissoko: 32

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Meanwhile the North London derby was the most stressful match - perhaps no surprise to anyone who's ever watched Arsenal Fan TV - with two in every five fans posting stressed tweets about the game.

This was closely followed by last season's title clashes between Liverpool and Manchester City. The recent rivalry between Chelsea and Spurs rounded out the top three:

1. Arsenal v Tottenham: 19.3%
2. Liverpool v Man City: 16.7%
3. Chelsea v Tottenham: 15.7%
4. Everton v Liverpool: 15.2%
5. Chelsea v Arsenal: 14.7%
6. Tottenham v West Ham Utd: 13.8%

Data for this research was provided using TensiStrength, an algorithm developed by Mike Thelwall, Professor of IT at Wolverhampton University, and has been optimised for general short social web texts, such as tweets.

TensiStrength estimates the strength of stress and relaxation expressed in short texts, even in informal language, by analysing the terms used that are related to stress, frustration, anxiety, anger and negativity.

For each match, Tensi-Stength looked at every tweet within a 24 hour period of the match, and found every tweet with the hashtag relating to the game as well as the most popular fan hashtag for each club.

Tweets were considered to be ‘stressed’ if they contained words relating to frustration, anger, anxiety, or other negative emotions.





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