To examine how many posts in your dataset contain toxic words or phrases, you can use a pre-compiled dictionary of toxic terms and swear words, developed as part of the following publication:
K. Hazel Kwon, & Anatoliy Gruzd. (2017). Is offensive commenting contagious online? Examining public vs interpersonal swearing in response to Donald Trump’s YouTube campaign videos. Internet Research, 27(4), 991–1010. https://doi.org/10.1108/IntR-02-2017-0072 [open access version]
First, download the dictionary file from an online data repository (make sure to select the CSV file prepared for Netlytic called ‘NETLYTIC_swear_dictionary.csv’).
Second, import the downloaded dictionary file into Netlytic using the Import button inside the “Dictionaries (Manual Categories)” window (as shown below).
![](https://i0.wp.com/netlytic.org/home/wp-content/uploads/2021/01/netlytic-manual-dict-1.jpg?resize=918%2C364&ssl=1)
Important: If you have already analyzed your dataset with this feature, you would need to click on the “Reset” button and then re-run the “Dictionaries (Manual Categories)” analysis for this new category to be included in the results.
![](https://i0.wp.com/netlytic.org/home/wp-content/uploads/2021/01/netlytic-manual-dict-reset.jpg?resize=520%2C436&ssl=1)
Once the analysis is ready, you can explore results using the treemap visualization (shown below) or export the resulting/labeled dataset as a CSV file using the Export option.
![](https://i0.wp.com/netlytic.org/home/wp-content/uploads/2021/01/netlytic-manual-dict-treemap.jpg?resize=918%2C437&ssl=1)
For more information about this type of analysis in Netlytic, see the following page: https://netlytic.org/home/?page_id=11101