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How to download your Twitter follower data using NodeXL Pro

This tutorial explains how you can download and analyze your Twitter follower data with NodeXL Pro.  Downloading follower data from Twitter is a simple task using the NodeXL Pro Import from Twitter Users List feature found in the NodeXL>Data>Import menu.  This feature will create an Excel spreadsheet containing a list of a user account, followers, the accounts it follows, and further metadata about the users.  These spreadsheets can be a useful way to keep track of the people you follow on Twitter if you want to find them again on other platforms and services.

NOTE! It is important to keep in mind that downloading data from accounts with large follower numbers can result in a request for an amount of data that is too large to handle for 1) your machine (lack of RAM), 2) Excel (1 million row limit) or 3) NodeXL (visual interface restricted to about 60k vertices).

NodeXL Pro importer menu

Download Twitter follower data from a single @user account

Just open the NodeXL Pro> Data > Import > From Twitter Users Network importer, enter the Twitter handle of your choice. Use the importer setup below and click OK. Downloading the data may take from a few seconds to a couple of hours depending on the follower counts of the analyzed account. In this example we have entered the NodeXL Twitter account.

Image of the NodeXL Pro Users Network importer

The resulting data set contains accounts that are following NodeXL in the Vertex1 column of the edges spreadsheet, while the accounts that are followed by NodeXL appear in the Vertex2 column.  Note that the API will not return information on when a follow was established.  The relationship column simply shows the date of the data collection.

NodeXL Pro Edges spreadsheet

Detailed information about the users like the follower counts are provided as metadata on the Vertices spreadsheet:

NodeXL Pro Workbook Vertices table

If you download and import this NodeXL options file (a.k.a. data recipe) and run it via NodeXL Pro>Graph>Automate, you will receive a network map like the one below.  Follow this link to view the data set in NodeXL Graph Gallery.  Further layouts with recipes can be viewed here (grid layout) and here (scatter plot layout).

A short video that documents the process of using a NodeXL Pro data recipe is available in this quick start guide.  Also click here for further information about Automating NodeXL Pro. The NodeXL data recipe runs each of the steps needed to process and analyze the Twitter data.

Twitter Users NodeXL Follower Network Harel-Koren layout

The network map may not look very useful in this case because it will always show a hub-and-spoke shape with the analyzed account in the center. The label at the top of the map shows the top ten word pairs in this network and is a pointer to the results from the text analysis.

Using the NodeXL text analysis features, we can analyze the text found in the Description column in the Vertices spreadsheet.  This text is created by each Twitter user to describe themselves and it is often useful to analyze to detect patterns. The detailed data is found in the Words and Word pairs spreadsheet:

When reviewing the Vertices spreadsheet, you can sort the column “Reciprocated Vertex Pair Ratio” to find all of the users that are both following and being followed by the NodeXL account.

Alternatively you can look at the metrics In-Degree and Out-Degree. An Out-Degree of 1 means that the account is following the NodeXL account, while an In-Degree of 1 means that an account is also being followed.

The usernames and descriptions may be enough information to reconstruct the collection of people your account follows and which follow you.  Having a local file with this data can be a useful asset as social media platforms like Twitter go through significant changes.

For further analysis of the data you should consider creating a semantic network analysis and map from the Word Pairs spreadsheet as explained in this tutorial.

Semantic network map of NodeXL Follower descroptions


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