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02_​Analyzing_​Twitter_​Data

Twitter Data Analysis
Twitter Data AnalysisThis workflow examines a sample of tweets from the days surrounding the scottisch referendum for independence in 2014 [1]. After reading the data from a localdatabase, basic text processing is used to extract hashtags from the dataset and term frequencies calculated and used to build a tag cloud. Subsequently, hashtagtrending 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 mostinfluential social graph surrounding this issue. Note the workflow includes a report which can be edited and viewed from the KNIME Reporting perspective (Hint: click the bar chart button next to the zoom indicator above)[1] http://en.wikipedia.org/wiki/Scottish_independence_referendum,_2014 How to open the reportIn order to see the report execute the entire workflow andthen click "Open the report" button in the toolbar. The Twitter API Connector requires API keys andaccess tokens to execute successfully. Togenerate these you will need to go to your twitteraccount at dev.twitter.com and register yourapplication under "My Applications". The API keyshould be immediately available and accesstokens may be generated and revoked as needed.Both should be available from the API Keys tab ofthe page for your application.In case you do not have Twitter API keys and accesstokens at hand, there is a data dump stored withinthe workflow. This data will be used, if querying ofthe Twitter API fails due to invalid credentials (seeAnalyze Network metanode for further details). API KeyConnect to DBTheme River of HashtagsInfluencial Usersgenerate ribbon positionsTopicsRetweet NetworkTop 25 TweetersTag Cloud Twitter APIConnector Pivot #tagsto columns SQLite Connector Text Processing R View (Table) Network Viewer ThemeRiverProcessing Image to Report Image to Report Data to Report Summary Stats Image to Report Database Reader Analyze Network Twitter Data AnalysisThis workflow examines a sample of tweets from the days surrounding the scottisch referendum for independence in 2014 [1]. After reading the data from a localdatabase, basic text processing is used to extract hashtags from the dataset and term frequencies calculated and used to build a tag cloud. Subsequently, hashtagtrending 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 mostinfluential social graph surrounding this issue. Note the workflow includes a report which can be edited and viewed from the KNIME Reporting perspective (Hint: click the bar chart button next to the zoom indicator above)[1] http://en.wikipedia.org/wiki/Scottish_independence_referendum,_2014 How to open the reportIn order to see the report execute the entire workflow andthen click "Open the report" button in the toolbar. The Twitter API Connector requires API keys andaccess tokens to execute successfully. Togenerate these you will need to go to your twitteraccount at dev.twitter.com and register yourapplication under "My Applications". The API keyshould be immediately available and accesstokens may be generated and revoked as needed.Both should be available from the API Keys tab ofthe page for your application.In case you do not have Twitter API keys and accesstokens at hand, there is a data dump stored withinthe workflow. This data will be used, if querying ofthe Twitter API fails due to invalid credentials (seeAnalyze Network metanode for further details). API KeyConnect to DBTheme River of HashtagsInfluencial Usersgenerate ribbon positionsTopicsRetweet NetworkTop 25 TweetersTag Cloud Twitter APIConnector Pivot #tagsto columns SQLite Connector Text Processing R View (Table) Network Viewer ThemeRiverProcessing Image to Report Image to Report Data to Report Summary Stats Image to Report Database Reader Analyze Network

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Created by: knime
Created at: 2015-02-18
On NodePit since: 2020-09-21
Last update: 2024-12-21
Created with KNIME version: v3.7.1
Tags: TwitterNLPtext processingNatural Language Processinggraph analysisnetwork analysissocial media

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