Diving Deep into Docket Reports

Expounding on the notion of using a word cloud and concordance on docket entries by examining Thomas Reuters Enterprise et al v. ROSS Intelligence Inc. (C.A. No. 20-613-LPS).

By Aamir Abdullah

As previously noted, docket reports may provide a decent snapshot for a given legal case. However, to gleam a view of that snapshot, the inquirer may be required to read through multiple pages of docket entries. And unfortunately, the effort of reading through the pages of docket entries may only yield a small glimpse of what has actually transpired in a legal matter. 

There are tools that exist to make digesting each docket entry, and for that matter court filings, an easier task. One method is to let someone else do the work. A person can simply wait for someone else to summarize a case for them. Institutions exist that currently do this. LexisNexis, Westlaw, and reputable news outlets do a wonderful job summarizing various high points in legal matters. 

Another available method may be to run docket entries through a word cloud or concordance. This novel idea might help with digesting the totality of the docket entries. This brief blog post is divided into 3 key sections. The first section provides the reader a refresher on docket reports. The second section provides and examines an up-to-date word cloud for the first 73 docket entries of the Thomas Reuters Enterprise et al. v. ROSS Intelligence Inc. (C.A. No. 20-613-LPS) case. Finally, the last section will conclude with some parting thoughts from the author. 

Rewind, What’s a Docket Entry?

My previous post provides an overview of docket reports. In summary, a docket report is comprised of three main parts. The first part provides the titles of the case. The second part provides information concerning the parties, including the attorneys. The third, and arguably most important part, is the docket entries. 

In short, docket entries for a particular case provide information on the specific court filings submitted within that case. The information provided includes: 1) the filing entry number, the date of the filing, and a brief description. The description summarizes the information contained within a filed document. A filed document may be a multi-page PDF filled with arguments, legalese, and the like. E.g., briefs, initial pleadings, and etc. 

The docket entry summary usually includes: 1) the type of filing, 2) the name of the filing party, and 3) a statement summarizing the contents of the filing. E.g., see Figure 1. 

Figure 1: Docket Entry 6, filed on May 6, 2020, noting that this filing type is a Summons returned to the Plaintiff, Thomas Reuters Enterprise Centre GmbH, indicating that Defendant, Ross Intelligence Inc., was served on May 6, 2020 by attorney Mr. Blumenfeld on behalf of the Plaintiff.

Press Play! 

Armed with a basic understanding of docket reports, let’s turn our attention to the Thomas Reuters Enterprise et al. v. ROSS Intelligence Inc. case (“West v. Ross”). This case is still on-going. The docket report can be found in a variety of locations. For this post, the author examined the docket report from Bloomberg Law. Printed out, the complete docket report is 16 pages long. Within the docket report, there are 73 docket entries. The 73 docket entries take up roughly 9 pages. 

Compared to the enumerable number of pages filed in the case, 9 pages does not seem terribly excessive. But, to a casual inquirer, 9 pages may still be a hurdle. This is especially true given most people’s short attention span and busy schedules. 

Word clouds can help condense the 9 pages of docket entries into a simple image comprised of words. First, one should get familiar with word clouds. Then, we should examine what we see from simply copying and pasting the content of the docket entries into a word cloud application. 

Head in the Clouds

The basics of a word cloud are simple. Essentially, an end-user inputs words into a word cloud application, the application uses an algorithm to determine the number of times words appear within the text, then the application churns out a “cloud” of the most used words from the provided text. The larger, bolder, the word appears in the cloud, the more that word is being used. 

Figure 2: Word cloud pulled from the text of the docket entries in the Westlaw v. ROSS case allowing numbers to be included within the output image.
Figure 3: Word cloud pulled from the text of the docket entries in the Westlaw v. ROSS case without numbers included within the output image.

Some word cloud applications allow the end-user to customize the output text. Some customizable features include: removing common words, including or excluding numbers, and altering word case. At the very least, these are the features offered in the application used to create the word clouds in this post and the last post. 

Above are 2 word clouds. The first word cloud, Figure 2, includes numbers, but the second word cloud, Figure 3, omits numbers. The input text for both Figure 2 and Figure 3 are the exact same. 

Hitting Some Turbulence 

When looking at either image, three key takeaways are apparent. First, it is clear that party names are the most used word in the docket entries. The petitioner, defendant, and judge appear prominently in both word clouds. Next, it is clear that action verbs are also heavily featured. Here, words like “filed,” “ordered,” and the like take up valuable landscape that do not really provide insight to what was filed, ordered, or the like. Lastly, it is clear that names of the filing party are also prominently shown. Here, one should notice the names of the filing attorneys and judges.


Clearly some refinement needs to be made in order to use word clouds to examine docket entries in a meaningful way. Although we saw the most prevalent words within the docket entries, we could not decipher what actually transpired in the case. In the future, it may be beneficial to take a few additional steps prior to creating word clouds. 

First, the words comprising the docket entries should be culled. Beyond removing common words and numbers, things like titles should be removed. E.g. attorney, judge, and the like. 

Second, the names of people making filing/decisions should be removed. These names are not particularly helpful because a common observer does not know who these people are. E.g. “Michael,” “Flynn,” and etc. 

Beyond these two steps, there may be more that needs to be done before using word clouds to examine docket entries. Or a new perspective may need to be taken… 


Notes Between Us (NBU) is a blog about conversations and topics of interest to the writers. The writers are expressing their personal opinions solely. Their essays represent their personal beliefs and not that of their workplaces or any organization they are associated with.