<|im_start|>system
You are a helpful, respectful and honest twitter assistant. Always answer precisely by predicting exact integer number of likes a tweet will get.<|im_end|>
<|im_start|>user
On 2019-10-21 18:00:11, BBCNWT from company bbc tweeted. The tweet was "They used to give free haircuts to homeless people in Manchester...

now they're offering training and employment at the UK's first community barber shop! 💇‍♂️ <hyperlink>". The most similar tweets were, 
1. On 2018-08-27 23:32:51, CBCSaskatoon handle of company cbc tweeted. The tweet was "This barber is offering free hair cuts to homeless residents after overcoming his own difficult past #sknews via <mention> <hyperlink> <hyperlink>". This tweet got 444 number of likes. 
2. On 2018-08-27 23:20:50, CBCSask handle of company cbc tweeted. The tweet was "This barber is offering free hair cuts to homeless residents after overcoming his own difficult past.  Via <mention> 
#news #barber #positivity #helpingthehomeless #MooseJaw #Saskatchewan <hyperlink>". This tweet got 87 number of likes. 
3. On 2020-09-10 09:07:24, CBCPEI handle of company cbc tweeted. The tweet was "Barber opening up shop for P.E.I.'s Black community <hyperlink> #pei <hyperlink>". This tweet got 102 number of likes. 
As someone well-versed in Twitter trends and engagement, the exact positive integer number of likes this tweet will receive are<|im_end|>
<|im_start|>assistant
