in Data Science, Results, Twitter Data Mining

Word Cloud

English version and some details below the image keep scrolling!

Lista tagów zawartych w tweetach zebranych w okresie wakacji (Czerwiec – Sierpień). Tweety były filtrowane słowem ‘polityka’.

Clustering twitter data is not easy. I know that now :).  A single tweet is mostly a noise. So at the end you will get a sparse matrix of corpus with density far below 1%.  Simply if all corpus contains around 50 000 words (dimensions) but a single tweet has only 10 words (and probably only one or two has some meaning). Lots of noise and sparsity. And finally clustering like k-means put all tweets to one big cluster.

So I decided to change approach and try get something different from collected data.

On my first attempt was to try make words cloud with hashtags.

To do it I used nice python module:

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This image was done on twitter data collected during June, July and August.the data was filter by polish word ‘polityka’.

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