Insight 2016B final demo

1. #WhatTheHash:
Twitter Hashtag Recommender
Emma Ideal

7. How can I find actively trending hashtags that are relevant for my tweet?

8. DATA MODEL
Train word2vec model
50 million recent English tweets
from the US/Canada
PCA

9. Warriors vs the Cavs!

10. vector mean
Warriors vs the Cavs!

11. Extract most recent 8 hours
of tweets with hashtags

12. Warriors vs
the Cavs!
User #nba #cavs #ilovecake .....
Extract most recent 8 hours
of tweets with hashtags

13. User #nba #cavs #ilovecake .....
similarity score
= cosine
similarity
0.865 0.795 0.144
Extract most recent 8 hours
of tweets with hashtags

16. 50% of the time, the actual hashtag used is in
my top 10 recommendations

17. Emma Ideal

20. Hashtag Popularity
For each hashtag:
1) popularity = the number of tweets the hashtag has
appeared in
2) Take the log10 of the popularity
3) Squash range to [0.8, 1]
For the relative popularity displayed on webpage:
1) popularity = the number of tweets the hashtag has
appeared in
2) Take the log10 of the popularity
3) Normalize to [0, 1]
4) Slice it so that:
1 star: < ~10 tweets
2 stars: < ~100 tweets
3 stars: < ~500 tweets
4 stars: < ~3000 tweets
5 stars: > ~3000 tweets

21. cosine similarity
x
# user’s search words in tweets for hashtag
# words in user’s search
x
Hashtag score =
hashtag popularity
Cavs
vs
User
#cavsWarriors
basketball
play