First Pass Review: Synonym Searching Your Opponent’s Data

Yesterday, we talked about the use of First Pass Review (FPR) applications (such as FirstPass™, powered by Venio FPR™) to not only conduct first pass review of your own collection, but also to analyze your opponent’s ESI production. One way to analyze that data is through email analytics to see the communication patterns graphically to identify key parties for deposition purposes and look for potential production omissions.

Synonym Searching

Another type of analysis is the use of synonym searching. Attorneys understand the key terminology their client uses, but they often don’t know the terminology their client’s opposition uses because they haven’t interviewed the opposition’s custodians. In a product defect case, the opposition may refer to admitted design or construction “mistakes” in their product or process as “flaws”, “errors”, “goofs” or even “flubs”. With FirstPass, you can enter your search term into the synonym searching section of the application and it will provide a list of synonyms (with hit counts of each, if selected). Then, you can simply select the synonyms you wish to include in the search. As a result, FirstPass identifies synonyms of your search terms to broaden the scope and catch key “hits” that could be the “smoking gun” in the case.

Tomorrow, I’ll talk about the use of fuzzy searching to find misspellings that may be commonly used by your opponent or errors resulting from Optical Character Recognition (OCR) of any image-only files that they produce. Stay tuned! 🙂

In the meantime, what do you think? Have you used synonym searching to identify variations on terms in an opponent’s produced ESI? Please share any comments you might have or if you’d like to know more about a particular topic.

First Pass Review: Of Your Opponent’s Data

In the past few years, applications that support Early Case Assessment (ECA) (or Early Data Assessment, as I prefer to call it) and First Pass Review (FPR) of ESI have become widely popular in eDiscovery as the analytical and culling benefits of conducting FPR have become obvious. The benefit of these FPR tools to analyze and cull their ESI before conducting attorney review and producing relevant files has become increasingly clear. But, nobody seems to talk about what these tools can do with opponent’s produced ESI.

Less Resources to Understand Data Produced to You

In eDiscovery, attorneys typically develop a reasonably in-depth understanding of their collection. They know who the custodians are, have a chance to interview those custodians and develop a good knowledge of standard operating procedures and terminology of their client to effectively retrieve responsive ESI. However, that same knowledge isn’t present when reviewing opponent’s data. Unless they are deposed, the opposition’s custodians aren’t interviewed and where the data originated is often unclear. The only source of information is the data itself, which requires in-depth analysis. An FPR application like FirstPass™, powered by Venio FPR™, can make a significant difference in conducting that analysis – provided that you request a native production from your opponent, which is vital to being able to perform an in-depth analysis.

Email Analytics

The ability to see the communication patterns graphically – to identify the parties involved, with whom they communicated and how frequently – is a significant benefit to understanding the data received. FirstPass provides email analytics to understand the parties involved and potentially identify other key opponent individuals to depose in the case. Dedupe capabilities enable quick comparison against your production to confirm if the opposition has possibly withheld key emails between opposing parties. FirstPass also provides an email timeline to enable you to determine whether any gaps exist in the opponent’s production.

Tomorrow, I’ll talk about the use of synonym searching to find variations of your search terms that may be common terminology of your opponent. Same bat time, same bat channel! 🙂

In the meantime, what do you think? Have you used email analytics to analyze an opponent’s produced ESI? Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Searching 101: Sites for Common Misspellings

Yesterday, we talked about the importance to include misspellings when searching for relevant ESI to broaden the search to retrieve potentially responsive files that might be otherwise missed and the use of “fuzzy searching” (with a product like FirstPass™, powered by Venio FPR™ that supports this capability) to identify variations as potential misspellings within the collection. Another way to identify misspellings is to use a resource that tracks the most typical misspellings for common words.

Examples of Sites

At, you can check words against a list of over 10,000 misspelled words. Simply type the correct word into the search box with a “plus” before it (e.g., “+management”) to get the common misspellings for that word. You can also search for misspelled names and places.

Wikipedia has a list of common misspellings as well. It breaks the list down by starting letter, as well as variations on 0-9 (e.g., “3pm” or “3 pm”). You can go to the starting letter you want to search, then do a “find” on the page (by pressing Ctrl+F) and type in the string to search. and are two other examples of sites for searching for common misspellings. Not all sites have the same misspellings, so it’s good to check multiple sites to comprise a comprehensive list. Each site provides an ability to search for your terms and identify common misspellings for each, enabling you to broaden your search to include those variations and most of these sites are updated regularly with new common misspellings.

Using Fuzzy search or sites with typical misspellings for your terms is one method of ensuring a more diligent eDiscovery search process by retrieving additional “hits” that might otherwise be missed. Over the weeks to come, we’ll talk about others.

In the meantime, what do you think? Are you aware of other sites to find common misspellings? Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Searching 101: It's a Mistake to Ignore the Mistakes

How many times have you received an email sent to “All Employees” like this? “I am pleased to announce that Joe Smith has been promoted to the position of Operations Manger.”

Do you cringe when you see an email like that? I do. I cringe even more when the email comes from me, which happens more often than I’d like to admit.

Of course, we all make mistakes. And, forgetting that fact can be costly when searching for, or requesting, relevant documents in eDiscovery. For example, if you’re searching for e-mails that relate to management decisions, can you be certain that “management” is spelled perfectly throughout the collection? Unlikely. It could be spelled “managment” or “mangement” and you would miss those potentially critical emails without an effective plan to look for them.

Finding Misspellings Using Fuzzy Searching

How do you find them if you don’t know how they might be misspelled? Use a search tool like FirstPass™, powered by Venio FPR™ that supports “fuzzy” searching, which is a mechanism by finding alternate words that are close in spelling to the word you’re looking for (usually one or two characters off). FirstPass will display all of the words – in the collection – close to the word you’re looking for, so if you’re looking for someone named “Brian”, you can find variations such as “Bryan” or even “brain” – that could be relevant. Then, simply select the variations you wish to include in the search. Fuzzy searching is the best way to broaden your search to include potential misspellings and FirstPass provides a terrific capability to select possible misspellings to review additional potential “hits” in your collection.

The most popular TV series all use “cliffhangers” to keep the audience hooked, so tomorrow, I’ll talk about sites available to identify common misspellings for terms as another way to broaden searches to include mistakes. 🙂

In the meantime, what do you think? Do you have any real-world examples of how fuzzy searching has aided in eDiscovery search and retrieval? Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Searching 101: Don’t Get “Wild” with Wildcards

Several months ago, I provided search strategy assistance to a client that had already agreed upon several searches with opposing counsel. One search related to mining activities, so the attorney decided to use a wildcard of “min*” to retrieve variations like “mine”, “mines” and “mining”.

That one search retrieved over 300,000 files with hits.

Why? Because there are 269 words in the English language that begin with the letters “min”. Words like “mink”, “mind”, “mint” and “minion” were all being retrieved in this search for files related to “mining”. We ultimately had to go back to opposing counsel and negotiate a revised search that was more appropriate.

How do you ensure that you’re retrieving all variations of your search term?

Stem Searches

One way to capture the variations is with stem searching. Applications that support stem searching give you an ability to enter the root word (e.g., mine) and it will locate that word and its variations. Stem searching provides the ability to find all variations of a word without having to use wildcards.

Other Methods

If your application doesn’t support stem searches, shows list of words that begin with your search string (e.g., to get all 269 words beginning with “min”, go here – simply substitute any characters for “min” to see the words that start with those characters). Choose the variations you want and incorporate them into the search instead of the wildcard – i.e., use “(mine or “mines or mining)” instead of “min*” to retrieve a more relevant result set.

Some applications let you select the wildcard variations you wish to use. FirstPass™, powered by Venio FPR™, enables you to type in the wildcard string, display all the words – in your collection – that begin with that string, and select the variations on which to search. As a result, you can avoid all of the non-relevant variations and limit the search to the relevant hits.

So, what do you think? Have you ever been “burned” by wildcard searching? Do you have any other suggested methods for effectively handling them? Please share any comments you might have or if you’d like to know more about a particular topic.