Today we will be working with the Netlytic platform. Netlytic is described as a community-supported text and social network analysis platform. We will use Netlytic to collect a dataset of social media posts and analyze them using tools within the platform.
Log in to Netlytic: https://netlytic.org/.
Click on My Account.
Click “Sign in with Twitter” to link your Twitter account to Netlytic.
Click “Authorize App”
Click on “New Dataset.” The base level Netlytic will allow you to create and store up to 3 datasets.
Give the dataset a name.
Enter the keywords you wish to search. Note that Netlytic uses Boolean operators.
Select your search criteria.
Test your Query on Twitter to see what’s available.
When you’re done, select Import.
Note that Netlytic, like TAGS can only scrape tweets going back 7 days. Unlike TAGS, however, Netlytic can only scrape a small number of tweets.
Click Next Step.
You can download this dataset and continue collecting tweets or we can analyze the dataset inside Netlytic.
Click on Text Analysis.
Text analysis allows us to analyze the dataset based on a category. In this case, let’s run the analysis on the tweets themselves (“description”).
We can also analyze the tweets based on positive vs. negative words by selecting a dictionary. If you have existing dictionaries, you can add them. We will use the default.
Now let’s go to Network Analysis.
Nodes represent users, edges represent the search criteria you selected (i.e. retweets etc.).
You can also generate a statistical report of your dataset by clicking “Report.”
Now let’s try this with YouTube comments. Find a YouTube video you are interested in.
Name your dataset.
Provide a YouTube ID. This should be the number/letter combination after v = in the YouTube video’s browser address.
Click Import.
Follow the same processes as outlined above.
Finally, if you want to work with Reddit data, navigate to Communalytic and sign up. The site will only allow you to collect historical Reddit data going back 7 days at the free tier.
