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Twitter Data Analysis

Twitter NLP Text processing Natural Language Processing Graph analysis
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This workflow examines a sample of tweets from the days surrounding the scottisch referendum for independence in 2014 [1]. After reading the data from a local database, basic text processing is used to extract hashtags from the dataset and term frequencies calculated and used to build a tag cloud. Subsequently, hashtag trending is examined over time, with a notable post election surge in the #the45 movement. Additionally, network analysis is performed in order to look at the most influential social graph surrounding this issue.

External resources

  • @KNIME Twitter Nodes

Used extensions & nodes

Created with KNIME Analytics Platform version 4.3.1
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

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    KNIME Connectors for Common Databases Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

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    KNIME Interactive R Statistics Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

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    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

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    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

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    KNIME Network Mining Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

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    KNIME Reporting Runtime Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • Go to item
    KNIME Textprocessing Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

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    KNIME Twitter Connectors Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

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