Social Media Sentiment Analysis

This workflow can be found on the KNIME Hub: Clustering Social Media Community

This example shows how sentiment analysis can be performed on social media data using the KNIME Text Processing plugin.

The example workflow, Clustering Social Media Community, which you can download from the KNIME Hub.

It uses data from the Slashdot homepage which is provided by Fundación Barcelona Media4 (http://caw2.barcelonamedia.org/node/25). The original subset contains about 140,000 comments to 496 articles about politics from a total of about 24,000 users. To allow the example to run on any machine with 2G of memory, we have subset the data around one particular topic area ("interviews") to show the techniques.

The full example along with an explanation on text mining, combined with Network mining, is available in the white paper section.

Find out more about different approaches to sentiment analysis in these two tutorials:

Sentiment Analysis: A Tutorial

Lexicon-based Sentiment Analysis: A Tutorial


* The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher)

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