<|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 2019-10-31 18:11:00, Airbnb from company airbnb tweeted. The tweet was "In 1974, newlyweds Stu + Penney stopped by a local Bangor writer's book signing. Little did they know, this teacher (and soon to be bestselling horror author) would make a shining impact on their lives. 👻

Read about the "It" factor in Airbnb Magazine: <hyperlink> <hyperlink>". The most similar tweets were, 
1. On 2019-10-22 09:52:24, evanwilliams handle of company williams tweeted. The tweet was "This Airbnb review takes a really unexpected turn. <hyperlink>". This tweet got 112 number of likes. 
2. On 2018-09-03 22:23:02, cbcnewsbc handle of company cbc tweeted. The tweet was "Orange Shirt Day founder writes children's book about residential school experience <hyperlink> <hyperlink>". This tweet got 52 number of likes. 
3. On 2020-09-22 22:58:30, MNPDNashville handle of company metro tweeted. The tweet was "Have gently used children's books around the house? Please consider donating them this week so that they can be read anew! Our School Resource Officers are helping to get the books into the hands of eager readers. <hyperlink>". This tweet got 65 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
