Tracking “Gross Community Happiness” from Tweets
@danielequercia
offline & online
community deprivation well-being use of words
?
community deprivation well-being use of words
community deprivation well-being use of words
social media
social media
top-using city
London
3 match sentiment with (census) deprivation
2 classify sentiment of profiles
1 collect profiles & geo-reference them
Goal
community deprivation use of words
250K profiles in London (31.5M tweets)
3 seeds: newspaper accounts
1 collect profiles & geo-reference them
1,323 in London neighborhoods 573 in 51 neighborhoods
Word Count vs. Maximum Entropy
2 classify sentiment of profiles
Index of Multiple Deprivation
3 match sentiment with (census) deprivation
r=.350 word count r=.365 MaxEnt
predicting socioeconomic well-being with twitter
So what?
Theoretical Implications
Practical Implications
Limitations
Future (well, current & you could help)
1 beyond sentiment …
Look at the subject matter of tweets!
social media environment sports health wedding parties
Spanish/Portuguesecelebrity gossips
Linear Regression R2=.49 (49% of IMD variability explained)
2 complex buildings
3 tools for topical & sentiment analysis
4
4 urbanopticon (image of the city)
3 scalable tools
2 complex spaces
1 topical analysis
deadline: March 2
@danielequercia
