Using InfraNodus you can visualize the most often used keywords and their relationships from Twitter, so you can know what's happening in any public discourse.
For example, you can group certain users into a list and the visualization will let you see what those users are talking about and what is missing from their discourse (the structural gaps).
This information can be used to better understand a certain domain or to learn how you could enter the online discourse and what you could offer inside that is not yet there.
There are two ways to do it.
If you just want a quick analysis, you can simply choose the Twitter App from the Apps page and then enter your query (you can choose your preferred language) and see the results:
If you want more control of the settings, e.g. import a social network of Twitter accounts instead of the keywords or your public Twitter user lists (so you can understand what they are tweeting about), follow the instructions below:
Go to https://infranodus.com/twitter (you might need to log in to access this page.
You can also access this app from the Apps page.
By default the Twitter import app imports all the tweets that contain the search term or hashtag you specify.
However, if you click on + show advanced settings you can then choose the following option:
- tweets from a user’s twitter list
This is an especially useful option if you would like to import the data on several Twitter accounts, not only one. You could simply create a public list on Twitter of the accounts you're interested in and then visualize the tweets from that list using InfraNodus.
You can also additionally select whether you want to see only the hashtags, only the users or both the hashtags and the users. These options may be interesting if you would like to discover the most active profiles behind a certain discourse.
Once you selected the “tweets from a user’s twitter list” option, copy and paste the full URL into the
- “URL of the Twitter List”
field that will appear above.
For example, our Twitter account @noduslabs has a Twitter list of users that post about data visualization. This list is called Dataviz and its URL is
That means we will copy and paste the full URL into the URL of the Twitter List field.
Verify that the user name of the list’s owner is displayed correctly by clicking into it.
For example it would be
@noduslabs for the example above.
Choose the name of the graph you want to save the results to. If you’d like to separate the different results choose a unique name. If you want to add to the already existing one, just specify its name in the Context Graph field.
By default we extract the most recent 200 tweets. You can modify this parameter (max 300). Contact us to extend this on your account if you need more.
By default the system will import only the hashtags used in the list.
Sometimes this is not enough, so you can choose to import both the hashtags and the words to get a fuller picture of the discourse that happens within a certain list.
**Click “Visualize” **and wait for the next page to load.
If you don’t see anything within 30 seconds, reload the page (Ctrl + R or Cmd + R) or using the reload button in the top right menu.
You will see the graph of the tweets. For this graph below we used the tweets from our
https://twitter.com/noduslabs/lists/dataviz list with the option to show both the hashtags and the words.
You might be interested to read this post on How to Interpret and Read Graph Visualizations to make sense of the results.
In general, the bigger are the words, the more influential they are in the discourse of the users added in this particular list. If you use the same words you will seem “relevant” to the group, but you may be lost among the others.
The closer are the words, the more they are used together. If you try to use the same patterns you will be relevant to the group but you won’t offer anything new to the existing discourse.
The same color indicates the most prominent topics of words that belong together and are used in the same context.
Finally, if you want to identify a possible gap in the discourse, look out for the gaps in the graph. If you manage to link the two prominent terms or topics that have not been linked before, your contribution would be relevant to this particular list’s discourse.
If you click on the certain words you will see the tweets they were used in. (If you can’t see anything, click the blue button at the top right corner).
If a certain word is too obvious, click it first and then click the delete icon next to it at the top right corner to remove it.