The document discusses identifying trendsetters among Yelp users. Trendsetters are influential early reviewers who review popular businesses and have large networks. The presenter used k-means clustering on Yelp data to identify six user groups, and determined that the "Crème de la Crème" and "Elites" groups were most likely to be trendsetters based on their early reviews of popular businesses and large networks. Next steps could include badging trendsetters on Yelp and giving them incentives to try new businesses.
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Grow your real estate business by embracing the tools, techniques, and strategies top producers use to lead their markets! You deserve more in your career explore this PowerPoint presentation created by Jim Remley and then jump on to erealestatecoach.com for even more!
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Summary: Stretching a dollar is just as important as ever, especially for non-profits. Learn how the VMFA used private partners to make every dollar feel like three.
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2. Agenda
1. Why try to identify trendsetters?
2. Who is a trendsetter?
3. How did I identify trendsetters?
4. What do the results look like?
5. What next?
4. Why try to identify trendsetters?
• Trendsetters create valuable new content
• Trendsetters increase other users’
engagement
• Gain insight on how Yelp can create more
trendsetters in the future
5. Why try to identify trendsetters?
• Trendsetters create valuable new content
• Trendsetters increase other users’
engagement
• Gain insight on how Yelp can create more
trendsetters in the future
= more people will use Yelp
= ad revenue!
$$$
7. What’s in the data?
h"ps://public.tableau.com/profile/karissa.nane"a#!/vizhome/YelpBusinessDiversity/BusinessCounts
Very diverse
businesses
8. 5 separate datasets:
• Business (60K+)
• Reviews (1M+)
• User (366K+)
• Tip
• Check-in
What’s in the Yelp data?
9. Who is a trendsetter?
Early
reviewer
Popular
businesses
Huge
network
Trendsetters
10. Who is a trendsetter?
• Early Reviewer
– How soon does a Yelp user leave a review?
• Popular Businesses
– How well are the businesses they review doing?
• Huge Network
– How many people are listening to the
trendsetters?
11. Who is a trendsetter?
• Early Reviewer
• Popular Businesses
• Huge Network
Feature
engineering
12. Who is a trendsetter?
• Early Reviewer
• Popular Businesses
• Huge Network
Feature
engineering
25. What can Yelp do next?
• Give a badge to the trendsetters, so
other users know who they are and follow
them
• Give trendsetters gift cards to try out new
businesses as a form of marketing
26. What else can we do?
• Predict whether a new user will become a
trendsetter (supervised learning)
• Analyze effects on types of businesses
(restaurants, laundromats, doctors, etc.)
• Given more data…
– Perform longitudinal analysis
– Analyze user profile texts to detect bots