tag cloud is a visual representation of text data and is typically made up of single word tags. The frequency of each tag is usually represented by size or color.

I created the following tag clouds using Twitter’s API and two KNIME workflows. Twitter’s API returned 1379 tweets by searching the #browns hashtag. The Browns are currently in the news for firing both their head coach and GM, so I thought the hashtag would make a good candidate for tag clouds.


First Tag Cloud

Tag cloud number 1 is based on common keyword tags found in all 1379 tweets. I stripped usernames and URLs from the tweets before processing them. I then used KNIME’s POS Tagger node to assign parts of speech to each term. The resulting tag cloud highlights nouns in brown, verbs in orange, and adjectives in black. Larger words appear more often in the tweets that were analyzed.


Second Tag Cloud

Tag cloud number 2 is based on the same tweets and keyword tags. For this tag cloud, I used KNIME’s Named Entity Tagger node to tag terms as either organizations, locations, or people. The resulting tag cloud highlights people in brown, organizations in orange, and locations in black. Terms in green could not be identified by the tagger. As with the cloud above, the larger the font, the higher the tag frequency.


Interested in creating your own tag clouds? I’ll have instructions posted soon. Until then, feel free to leave a comment with your Twitter username and the hashtag you’d like analyzed. I’ll tag you with the results.

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