We’ve teamed up with the good people of Twizoo to announce the top 5 trending restaurants on Twitter each week in London. Twizoo is an app that gives restaurant recommendations based on what people are saying on Twitter, and analyses over 50,000 incoming tweets per week to determine which restaurants are attracting the most buzz.
Trending Restaurants 12-18 May 2016
Dalloway Terrace @DallowayTerrace
Check it out on Twizoo: https://www.twizoo.com/R529054/Dalloway-Terrace/
â€” Laila Loves (@LailaBlogs) May 17, 2016
â€” Katie Matthews (@XKatieMatthewsX) May 14, 2016
Check it out on Twizoo: https://www.twizoo.com/R011196/Ducksoup/
â€” Lucienne Simpson (@luciennesimpson) May 17, 2016
â€” Elizabeth Macgregor (@Lizzie_Mac_) May 14, 2016
Chucs Restaurant @bychucs
Check it out on Twizoo: https://www.twizoo.com/R529053/Chucs-Restaurant/
â€” Molly Ahmed (@MollyAhmed) May 17, 2016
â€” Gabriel Lovas (@gabriellovas) May 13, 2016
Check it out on Twizoo: https://www.twizoo.com/R324465/Mildreds/
â€” Natalie Mainwaring (@NatsMainwaring) May 15, 2016
â€” Alex Higson (@alexhigson) May 16, 2016
Mr Bao @mrbaouk
Check it out on Twizoo: https://www.twizoo.com/R527338/Mr-Bao/
â€” Dan Wong (@danoreowong) May 13, 2016
Oooh @MrBaoUK gorgeous meal last night. Can’t wait to return!
â€” jessica evershed (@jessevershed) May 11, 2016
Twizoo’s Techies Explain…
You’ve probably noticed on Twitter on the left hand side of your ‘Home’ page there’s a ‘Trends’ list. Twizoo has built the same thing, but solely for London restaurants. Our number crunching detects the rate of change of influential mentions on Twitter. For example, ‘Christmas’ is currently trending on Twitter, which means there’s been a spike of mentioning Christmas now compared with the rest of the year.
Applying this to Twizoo’s algorithms: if X restaurant usually gets on average 10 tweets per week, but this week it gets 32 tweets… that’s a pretty big change, so it’s a good indicator something notable is going on. The algorithm notes restaurants that have the highest rate of change and ranks them based on which places’ tweets are the most positive collectively and then it takes the top of those based on how influential the individuals are who tweeted. Simple see?
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