<|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 2019-09-09 15:30:27, USAID_Digital from company usaid tweeted. The tweet was "#DYK that women in developing countries are 14% less likely to own a mobile phone than their male counterparts? In our 2018 #DigitalDownload, we discuss some of the ways that digital supports self-reliance and #genderequality: <hyperlink> <hyperlink>". The most similar tweets were, 
1. On 2018-03-01 11:11:29, UnileverFoundry handle of company unilever tweeted. The tweet was "Our global research, ‘Scaling Up Diversity’ has highlighted issues of gender bias across every stage the #startup life cycle.

Read more about the research and what we’re doing to help drive positive change here: <hyperlink> <hyperlink>". This tweet got 79 number of likes. 
2. On 2018-04-18 00:52:04, CiscoSecure handle of company cisco tweeted. The tweet was "#DYK women contribute just under 60% of the wealth in the United States? 👌👌👌 #RSAC <hyperlink>". This tweet got 4 number of likes. 
3. On 2020-04-10 06:56:34, IndependentNGR handle of company independent tweeted. The tweet was "COVID-19 Worsening Gender Inequality — UN Chief <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
