Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
london.feels.website
Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
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Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#2Hi HN.
I've built a map that takes a geofenced stream of tweets and runs AFINN-111 sentiment analysis on them, and then displays them in real time on a map of London.
Negative sentiments are displayed as Red tweets, happy tweets are Blue.
The whole thing is built on node.js using node-tweet-stream, node-sentiment and socket.io. The frontend map is leaflet with stamen design's Toner tiles.
It's quite fun to watch, especially when there's a football match or a concert. If you click on the "follow tweets" checkbox, new tweets pop up as they arrive, although currently that makes the map pan north.
Thanks!
Dario.
Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#3Clicked through ~20 of them and the analysis was completely off in most cases.
Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#4Yeah, the the realisation of it is nice enough to look at, but the sentiment analysis (as always for these kinds of things) is pretty wonky.
Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#5Good job, expect I find colors pretty unintuitive - why red means negative? It's color definitly connected with love, anger, war etc. So blue is for cold or maybe not showing emotions. I would definitely rethink that. And senitment analysis not always work - get a tweet rated as "sweet" ended with ":(".
Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#6Could perhaps be more accurately retitled 'London claims to feel on social media' map. There's a lot of literature examining how people present themselves in such venues and how it's often an intentional communication (even if subconscious) to create a certain impression.
Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#7Hi HN. I've built a map that takes a geofenced stream of tweets and runs AFINN-111 sentiment analysis on them, and then displays them in real time on a map of London. Negative sentiments are displayed as Red tweets, happy tweets are Blue. The whole thing is built on node.js using node-tweet-stream, node-sentiment and socket.io. The frontend map is leaflet with stamen design's Toner tiles. It's quite fun to watch, esp…
Very nice. It also gives me the impression that people in the West End are certainly more angry (or have free time to be angry on twitter) during office hours than those in the City.
Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#8Yeah, the the realisation of it is nice enough to look at, but the sentiment analysis (as always for these kinds of things) is pretty wonky.
Yep, i realised that - but node-sentiment was pretty quick to implement and gives alright results, so it's a bit of a tradeoff.
Do you know of more accurate sentiment analysis services?
Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#9Good job, expect I find colors pretty unintuitive - why red means negative? It's color definitly connected with love, anger, war etc. So blue is for cold or maybe not showing emotions. I would definitely rethink that. And senitment analysis not always work - get a tweet rated as "sweet" ended with ":(".
well, i have to say the mapping of colours to concepts is highly cultural, so in some places it means anger, or war, or love or joy.
I chose red and blue because they're quite perceptually separated, so it's easy to point them out on the map.
Re: Show HN: London Feels – Sentiment-analysis of Londoners Tweets on a Map
#10Cool! Hey, that's very funny....
We did the same with Tweets and Surfing. http://devwax.herokuapp.com/ from the meetup: http://www.meetup.com/DevWax/. It was all done in a weekend with some drinking and surfing, so it's a bit rough. The trouble with surfing was that the locations are very disparate and hard to guess. Fun to have a go at though...
Are you in London? (We are)