tracking "gross community happiness" from tweets

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

twitter

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