<|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 2019-01-28 11:00:00, BofA_Business from company bank of america tweeted. The tweet was "Savita Subramanian will discuss #earnings on <mention> <mention> today at 6:30am ET <hyperlink>". The most similar tweets were, 
1. On 2018-09-24 19:31:44, SABCNews handle of company sabc tweeted. The tweet was "#CyrilRamaphosa on SA's economy in a nutshell <hyperlink>". This tweet got 192 number of likes. 
2. On 2019-03-28 16:56:10, SABCNews handle of company sabc tweeted. The tweet was "EFF commenting on economy <hyperlink>". This tweet got 274 number of likes. 
3. On 2020-03-10 03:13:35, IndependentNGR handle of company independent tweeted. The tweet was "Access Bank Assets Now N7.15trn, Posts N97.5bn Profit <hyperlink> <hyperlink>". This tweet got 0 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
