<|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 2018-02-12 18:01:05, BofA_Tips from company bank of america tweeted. The tweet was "Went a little overboard on the holidays? Here are 3 ways to bounce back from overspending. <hyperlink> <hyperlink>". The most similar tweets were, 
1. On 2020-12-11 16:00:08, USAA handle of company usaa tweeted. The tweet was "Tips on spreading holiday cheer without digging yourself deeper in debt - <hyperlink> <hyperlink>". This tweet got 30 number of likes. 
2. On 2018-12-12 16:00:02, DesjardinsGroup handle of company desjardins tweeted. The tweet was "Don't risk over spending this #HolidaySeason. Use our #PersonalBalanceSheet tool and keep track of all your finances in one single document. <hyperlink> <hyperlink>". This tweet got 1 number of likes. 
3. On 2019-01-15 14:30:00, amfam handle of company american family insurance tweeted. The tweet was "Did your budget take a hit this holiday season? Here are some tips to help you recover so you can start the New Year strong. <hyperlink> <hyperlink>". This tweet got 1 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
