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Automate NodeXL Pro > Automate your Twitter social media network analysis!

The following NodeXL Pro “data recipes” are designed to analyze Twitter network data with just a few clicks.  These files contain all options settings needed to automate the tasks required to create a full-scale social network and content analysis.

You can easily customize these data recipes to your own needs and save them for future use. You can learn how to automate NodeXL Pro by reading this pagelooking at this tutorial and/or watching this video.

Download the official NodeXL Pro recipe bundle below, then unzip and save the folder to your machine.

Twitter standard recipe

Twitter User Network 01 – standard

This recipe is designed for networks imported with all NodeXL Pro Twitter Data importers with a size of up to 5000 vertices. All relevant steps to conduct a full-scale social network analysis are performed. The graph shows an image and a label for every user in the network.

Vertex: Twitter User
Edges: Mentions, retweets, replies, follows
Vertex size: Betweenness centrality
Group clustering algorithm: Clauset-Newman-Moore
Group labels: Top 10 most frequently used hashtags
Content analysis: Top words/word pairs/URLs/domains/hashtags
Time series analysis: Yes
Sentiment language: English
Layout: Harel-Koren Fast Multiscale, Group-in-a-Box, Treemap

Twitter User Network 02 – large

This recipe is designed for Twitter networks larger than 5,000 vertices and is very similar to the standard recipe shown above. All relevant steps to conduct a full-scale social network analysis are performed. The main difference to the standard recipe is Vertex sizing by Indegree, and a label is shown only for users with an Indegree larger than 5.

Vertex: Twitter User
Edges: Mentions, retweets, replies, follows
Vertex size: Indegree
Group clustering algorithm: Clauset-Newman-Moore
Group labels: Top 10 most frequently used hashtags
Content analysis: Top words/word pairs/URLs/domains/hashtags
Time series analysis: Yes
Sentiment language: English
Layout: Harel-Koren Fast Multiscale, Group-in-a-Box, Treemap

Twitter User Network 03 – large / shapes

This recipe is designed for Twitter networks larger than 5,000 vertices and is very similar to both recipes shown above. All relevant steps to conduct a full-scale social network analysis are performed. Vertices are sized by Indegree, an image and a label is shown only for users with an Indegree larger than 5. When working with very large networks, this will speed up the visualization time because not all user profile images are collected and rendered.

Vertex: Twitter User
Edges: Mentions, retweets, replies, follows
Vertex size: Indegree
Group clustering algorithm: Clauset-Newman-Moore
Group labels: Top 10 most frequently used hashtags
Content analysis: Top words/word pairs/URLs/domains/hashtags
Time series analysis: Yes
Sentiment language: English
Layout: Harel-Koren Fast Multiscale, Group-in-a-Box, Treemap

Twitter User Network 04 – alternative layout

This recipe is designed for Twitter networks larger than 5,000 vertices and is very similar to both recipes shown above. All relevant steps to conduct a full-scale social network analysis are performed. Vertices are sized by Indegree, an image and a label is shown only for users with an Indegree larger than 5. When working with very large networks, this will speed up the visualization time because not all user profile images are collected and rendered.

Vertex: Twitter User
Edge: Mentions, retweets, replies, follows
Vertex size: Indegree
Group clustering algorithm: Clauset-Newman-Moore
Group labels: Top 10 most frequently used hashtags
Content analysis: Top words/word pairs/URLs/domains/hashtags
Time series analysis: Yes
Sentiment language: English
Layout: Harel-Koren Fast Multiscale, Group-in-a-Box, force-directed

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