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The NodeXL Series: Conducting a Twitter User Network Crawl (Part 6)

Per the prior entry, if a hashtag search is very time-dependent and ephemeral / transitory, the user accounts and relationships created around entities (people, organizations, companies, robots, and “cyborgs”) tend to be more stable.  While the research does not necessarily show that a follower / following sort of reciprocal relationship means that all Tweets are read and engaged, these do show a sense of some initial commitment and public declaration of a kind of relationship.  (Those interested I the research may find that there are surprises, such as that popularity and positive word-of-mouth does not necessarily translate to sales commitments.  Further, there is sufficient system gaming by using ‘bot and other accounts that a more accurate read of a user network requires some more digging and critical thinking analysis.)

First, it helps to pick a “target.”  A search on a search engine of an organization’s name “and Twitter” will often lead to the account information. For our purposes, we’ll go with the Centers for Disease Control and Prevention (CDC), in part because they have a clear social media strategy to engage their constituents.

A Limited Crawl of the CDCGov User Network on Twitter

The official Twitter account for the CDCGov site is https://twitter.com/CDCgov.  (Do read the fine print carefully to make sure that you haven’t landed on a farce site.  There are many pretenders, some not-so-subtle, and others very elusively so.)

Continue reading “The NodeXL Series: Conducting a Twitter User Network Crawl (Part 6)”

The NodeXL Series: Conducting a Hashtag Network Search of Twitter (Part 5)

Sometimes, it’s interesting to learn what is being Tweeted (micro-blogged) about particular topics in real time along with who is posting which messages.  NodeXL enables the extraction of individuals engaged in a particular hashtag-labeled microblogging conversation through Twitter’s application programming interface (API).  This entry will provide an overview of how this is done.

Hashtags

A hashtag is a snippet of text prefaced with a # (hashtag or pound) sign which indicates that the message is focused on a particular theme or topic.  In Twitter, the microblogging site, various Tweeted threads are collected around hashtags for coherent 140-character conversations from people from around the world.

A hashtag search of Twitter, then, involves the extraction of entities (Twitter accounts representing people, robots, and cyborgs) who have conversed around a particular topic. The application programming interface (API) used in NodeXL only extracts hashtag searches Tweeted in the prior week and a half.

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The NodeXL Series: Conducting a Crawl of Flickr for a Content Network (Part 4)

A related tags network on a content site shows the interrelationships between the textual metadata used to label particular images (or videos).  A content network may be built around a particular search term.  The tags are searched on a social media (sharing) platform, and instances of the term are discovered.  A graph is then created from the interrelationships between related terms.

Starting a Content Crawl of Related Tags on Flickr

To start a content crawl of related tags on Flickr, start up the NodeXL template.  Click on the NodeXL tab to open the ribbon

In the File area, click on “Import” to acquire the dropdown menu.  Highlight “From Flickr Related Tags Network…”

Continue reading “The NodeXL Series: Conducting a Crawl of Flickr for a Content Network (Part 4)”

The NodeXL Series: Visualizing NodeXL Graphs (Part 3)

To give a sense of the various types of graphs that may be “drawn” from data using NodeXL, this entry highlights some of the different types of graphs.  This entry will be created  using a data extraction from Twitter. All the graphs here will be taken from the same data set; the only differences in visualizations will come from the layout algorithms.   [This data crawl—more on this in later entries—was a 2-degree crawl of Pulitzer Prize-winning author Laurie Garrett’s (Laurie_Garrett) user network on the microblogging site Twitter, with an ego neighborhood limit of 100 persons (alters).  Her formal account has 3,768 Tweets, 228 following, and 2,558 followers.)

The Data Extraction

This data extraction required an over-night crawl because of Twitter-imposed limits per its application programming interface (API) and the size of the electronic social network.

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The NodeXL Series: Downloading NodeXL (Part 2)

Once you’ve made sure that your computer and version of MS Office (particularly Excel) is compatible with NodeXL, you may be ready to download this free add-in.

To download the NodeXL add-in, go to the CodePlex site.  At the top right is a button that reads “download.”

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The NodeXL Series: The NodeXL Graph Gallery (Part 1)

Intro Note:  NodeXL is an add-on to later versions of Microsoft Excel (on PCs, or virtual machine-enabled Macs), which enables the visualization of data in network diagrams.  It also enables the extraction of social media platform data from spaces such as Twitter, YouTube, Flickr, and in a fairly limited way, Facebook.  With additional work, this may be used to conduct analysis of email networks, wiki and blog networks, and even Internet site networks.  This series highlights some of the basic functionalities of NodeXL.

In the spirit of Web 2.0, the NodeXL team sponsors a NodeXL Graph Gallery to showcase the work of its members.  These graphs show a variety of data sets. They also suggest at a variety of types of research around social networks and electronic social networks.

At the top level of the site, 24 graphs are visible (albeit with some required scrolling).

A basic perusal of this site shows a wide range of types of network graphs.  There is pagination at the bottom to view other sets of graphs.

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