Category Archives: Social Media Metadata

September 21, 2023 · 2:04 PM

An Estimated 500,000 Litigation Matters Involved Social Media Evidence in the Past 12 Months

By John Patzakis

As we have mentioned many times, nearly every litigation matter involves social media evidence. If your case does not feature such important evidence, it is likely because you are not looking for it. By analogy, Taylor Swift’s music is all around us, but you won’t hear it unless you tune into it on the radio or your streaming music site of choice. Similarly, you have put some effort to tune into the torrential rivers of social media evidence.

To illustrate this point, we sought to identify some metrics reflecting the ubiquity of social media evidence in litigation matters. While this is an inexact science, we searched online legal databases of state and federal court decisions across the United States to identify the number of cases from the past twelve months where evidence from social networking sites played a significant role. The search was limited to five social networking sites: Facebook, LinkedIn, X/Twitter, Instagram, YouTube and TikTok for the period September 1, 2022, through August 31, 2023. The preliminary result was 5,623 cases. However, according to UCLA Law, less than 1 percent of litigation matters result or otherwise generate a published opinion, noting that “less than half of intermediate appellate opinions tend to be published. State trial court opinions are never published, and only a tiny fraction of federal trial (district) court opinions are published.”

So, by extrapolating the percentages, we very conservatively estimated that the 5,623 cases represented 1 percent of all cases involving social media evidence, bringing the actual estimated number to 562,300. We then employed a sampling method to determine that about 10 percent of the results were merely situations where the social media company was a named party or de minimis mentions — defined as cases with merely cursory or passing mentions of social media, so we pared down the results to an even half million.

This survey is an important data point establishing the ubiquitous nature of social media evidence and the importance of best practices technology like X1 Social Discovery to “tune in” to this evidence by searching and collecting social media evidence for litigation and compliance requirements.

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Filed under Authentication, Best Practices, Case Law, eDiscovery, eDiscovery & Compliance, law firm, Preservation & Collection, Social Media Investigations, Social Media Metadata

August 30, 2023 · 12:52 PM

Best Evidence Rule Requires Post-Level Collection for Social Media Evidence

By John Patzakis

The Best Evidence Rule, as codified in Federal Rule of Evidence 1002, provides that an original writing, recording, or photograph is required to prove the contents of the document. This rule was formulated in a paper document dominated era, and aimed to prevent fraud and inaccuracies that could arise from secondary or duplicate evidence. However, the prevalence of electronically stored information (“ESI”) prompted exceptions to this rule when it comes to computer-generated evidence. Specifically, FRE 1001(d) was drafted to provide clarification for how ESI was to be treated under the Best Evidence Rule: “For electronically stored information, ‘original’ means any printout — or other output readable by sight — if it accurately reflects the information.”

FRE 1001(d) means that for most forms of ESI, including electronic documents, emails, digital photos, and video files, an exact copy of those items will suffice under the Best Evidence Rule. And because it is very easy to create an exact copy of electronic evidence (as any eDiscovery practitioner who has ever “de-duped” ESI can attest to), the Best Evidence Rule has been almost forgotten in the ESI era. However, it is very different when it comes to screen shots of social media posts. Because screen shots are truncated images of the full native social media posts, they are not exact copies of the original as defined under FRE 1001(d). In fact, given the unfortunately extensive but erroneous reliance on screenshots of social media evidence, The Best Evidence Rule could be cited far more frequently by opposing counsel seeking to contest the admission of such evidence.

A case out of the federal courts in Texas addressed this issue head on. Edwards v. Junior State of America Foundation, is a civil litigation matter involving the intentional destruction (spoliation) of social media evidence. The plaintiff had deleted his Facebook account resulting in lost evidence critical to the case. The court cited an affidavit submitted by an eDiscovery expert witness who noted that when X1 Social Discovery was used to collect from the Plaintiff’s Facebook account, key evidence that existed prior to the litigation was missing because it had been deleted by the Plaintiff prior to the X1 Social Discovery collection.

As a result of the spoliation established in large part by the X1 Social Discovery examination, the Court imposed severe evidentiary sanctions on the plaintiff, including the exclusion of evidence and claims related to the destroyed Facebook data, and adverse jury instructions.

The plaintiffs’ had sought to offer screenshots as evidence of the Facebook communications instead of the deleted native files. The court ruled that the metadata and full context of the native files were essential to satisfy the Best Evidence Rule. The court held that screenshots were not an output that accurately reflected the substance and context of the native file, since they could not show that the messages were authentic, nor could they “be used to prove that Harper sent the Facebook Messages contained in the screenshots.” Failure to produce the native files prejudiced the Defendants, in part, because it deprived them “of the ability to substantiate or refute the authenticity of the alleged messages.” In a key passage the court states:

“Here, the screenshots will not suffice as an ‘original’ because the screenshots are not an ‘output’ that accurately reflects the information. Only native files can ensure authenticity. Additionally, although the Best Evidence Rule allows for an original ‘photograph’ to prove the contents of the photograph, this does not mean that the screenshot here can be used to prove that Harper sent the Facebook Messages contained in the screenshots.”

Edwards demonstrates that the collection and preservation of full native social media posts is vital to both that evidence’s authentication and obtaining the full context and substance of the posts under the Best Evidence Rule. The court found that screenshots, which truncate social media posts and omit key metadata, do not suffice. As a result, attorneys should be aware that courts are unlikely to find that screenshots alone are sufficient to authenticate a social media post and will likely insist on the native files. To ensure this data is collected defensibly, attorneys should work with best practices software and methods to preserve and collect social media evidence and underlying metadata so that they can be properly authenticated and admitted in court.

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Filed under Best Practices, Case Law, Corporations, ECA, eDiscovery, ESI, law firm, Preservation & Collection, Social Media Investigations, Social Media Metadata

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June 13, 2023 · 10:14 AM

Law Firms Are Demanding Native, Post-Level Collection of Social Media Evidence to Support Standard Review and Analytics Workflows

By John Patzakis

Two months ago, X1 launched version 7 of our X1 Social Discovery social media and web collections solution. This major upgrade features a new cutting-edge Instagram connector, along with our revamped Facebook support, where all our users now have native post-level collection and parsing to ensure accuracy, key metadata collection, court authentication, and evidentiary completeness of the collected data. As stated by X1 CEO Larry Gill: “Nothing short of those capabilities is acceptable and that is why I can confidently say that X1 Social Discovery is the only solution in the industry capable of delivering all those requirements.”

Version 7 has been a huge success, with record sales seen since its release. In fact, in speaking recently with several attorneys at top law firms, it’s very clear both how important such native post-level collection is in order to support standard attorney review and data analytics workflows, and that there is a disconnect with some practitioners who are utilizing alternative web plug-in based screen shot generation tools that do not support these now basic but essential requirements.

It is very important to understand the unique ability of X1 Social Discovery to perform post-level native collection of each social media post. This means that the social media post is collected in its native format and parsed so that it has its own associated metadata, photos, indexed text and in-line comments. This allows for the individual Facebook or Instagram posts, Tweets, etc. to be searched, filtered, tagged, and exported individually at the post-level with all associated metadata and comments inline. The ability with X1 to tag, sort, authenticate (with individually associated hash values), and upload individual posts by up to thousands at a time without manual processing into an attorney review platform is essential for an efficient and scalable workflow. And X1 is the only solution that can deliver this critical functionality.

In contrast, the web plug-in tools generate flat file image PDFs as its final output. So, if there are 30 posts that are in a feed, a single monolithic image PDF will be generated as the collection output. These bulk screenshots are of very limited value as they are not collected in native format, retain no post-level metadata, and are not searchable (absent a secondary and inferior OCR process). This output is practically useless for a review platform (as the entire output is one object).

Additionally, as we all know, AI-based analytics is a game-changing capability that is now a standard feature of the leading eDiscovery review platforms. However, ESI must be properly collected in order to support such AI. Semantic AI engines ingest and analyze the extracted text and metadata of individual emails, electronic documents, social media posts and web pages. Only X1 Social Discovery collects full text & post-level metadata and performs and maintains the collection at the individual object-level, all of which is necessary to support upstream AI analysis. Using the web plug-in tools is a decision to not use AI on your case for social media and website evidence.

Another key differentiator is that X1 Social Discovery is a robust software application that can be installed on a computer, including virtual cloud servers. This enables X1 to take advantage of the full CPU and RAM resources available to address heavy workloads as needed with multi-threading capabilities. As a result, X1 can run multiple collections at the same time, auto-expand and auto-scroll across thousands of posts, and collect posts with thousands of comments. For instance, a web crawl collection, a Facebook collection, and a YouTube collection can be run at the same time. Data can be reviewed and analyzed immediately as it populates.

Further, social media collections often involve thousands of posts with hundreds of associated comments and multiple images. This requires adequate resources to perform auto-expanding and auto-scrolling of pages, comments, and images. X1’s architecture provides for such a scalable workflow.

In contrast, the web plug-in tools are web browser plug-ins that face very limiting performance ceilings and functionality constraints inherent to any such plug-in. Many users report limitations beyond capturing a few dozen posts at a time at best, with an inability to capture all comments when they number in the hundreds or numerous clustered images in thumbnail format. For this reason and many others, the web plug-in tools are generally considered a low market tool for one-off small collections.

Additionally, the legal evidentiary defensibility provided by X1 Social Discovery is in a class by itself. This is because X1 captures over a dozen unique item-level metadata fields, including the URL of the individual post (not bulk feed), User ID, Post ID, date stamps and other key metadata. Importantly, each post, which is an individual object, has its own hash value generated at the time of collection. So, when thousands of individual posts, YouTube videos, and web pages are collected into a case, and there is then a need to provide a subset of those items into a review platform or produced in discovery, the hash value and post-level metadata for each item remains intact.

The web plug-in tools only record general URLs of the bulk collection, a hash of the entire “all or nothing” bulk PDF export containing up to dozens of individual posts, with no individual hash values or metadata fields specific to any of those posts. There is an important distinction here between object-level metadata (i.e. each post) and metadata associated with the bulk feed image. If the web plug-in tools capture 50 posts in a single image feed, and the client may only want 4 of them moved into a review platform for further review, there is no way to do that except for taking secondary Snagit-type screenshots, rendering the chain of custody broken and the hash value inapplicable.

Finally, the court in Edwards v. Junior State of America Foundation, No. 4:19-CV-140-SDJ, (US Dist. CT, E.D. TX 2021), specifically ruled that only HTML or JSON social media collections are defined as “native file collection.” Flat PDFs are not.

To see this critical and unique functionality in X1 Social Discovery v7, please watch our product tour on-demand. Alternatively, we would welcome the opportunity to brief you and your colleagues directly. Please contact us to speak with a member of the X1 Team.

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April 24, 2023 · 3:56 PM

X1 Introduces Cutting-Edge Instagram Support with X1 Social Discovery Version 7

By Larry Gill

Since I joined the X1 team last year as CEO, I have made it my priority to double down on our support and expansion of our X1 Social Discovery solution. To that end, I am excited to announce that we have just launched version 7 of X1 Social Discovery, social media and web collections solution, which includes a new cutting-edge Instagram connector, along with our revamped Facebook support, where all our users now have native post-level collection and parsing to ensure accuracy, key metadata collection, court authentication, and evidentiary completeness of the collected data. Nothing short of those capabilities is acceptable and that is why I can confidently say that X1 Social Discovery is the only solution in the industry capable of delivering all those requirements.

Over the past year, I have spoken to many of our customers and prospects about what they need to support their social media eDiscovery collections and investigations. One thing that became clear: post-level native file collection for social media evidence, including Instagram, is essential.

Other tools simply provide bulk flat file screen shots of social media feeds, and are of very limited value, as they merely provide a screenshot PDF image file without searchable text or metadata, other than what is visible on the image itself. This does not meet the needs of attorneys and paralegals seeking to leverage and admit key social media and website evidence into their cases. For this reason, X1 has put in the work and R&D investment, and, as CEO, I am committed to doing so on an ongoing basis, so that our users would have native post-level collection and parsing as required.

X1 Social Discovery is the only solution to provide native file, post-level Instagram support, and in a manner that is fast and scalable. This enables the following top 5 key benefits for Instagram collections:

  1. Fast and Automated Instagram Feed Capture. X1 Social Discovery v7 captures hundreds of Instagram posts with assorted comments per hour. We have successfully captured several thousand posts in our testing, including individual posts that have hundreds of associated comments and replies. This level of performance is simply impossible with “web plug in” tools.
  2. Post-Level Collection, Filtering and Production. The ability to search, tag, sort, authenticate (with their own hash value), and produce individual Instagram posts with X1 is essential for an efficient and effective workflow. Other tools require “all or nothing” production & hash of the flat PDF output.
  3. Federated Search and Review. With X1, multiple Instagram, Facebook, Twitter, YouTube and web page collections can now be searched, sorted, and reviewed in a unified manner. No other tools on the market have an integrated review capability.
  4. Robust Post-Level Metadata Capture. X1 Captures over a dozen unique item-level metadata fields for an individual Instagram post. Other tools only record general URLs of the bulk collection, a hash of the entire “all or nothing” bulk PDF export containing up to hundreds of individual posts, with no individual hash values or metadata fields specific to any of those posts.
  5. Deep Integration with Relativity for Review. X1 custom-developed a Relativity .RAP file that enables social media data (now including Instagram) to be displayed natively – at the post-level — in full context in Relativity, the same as it appears in X1 Social Discovery. All metadata is overlayed, and the comments are kept in line and in context. Importantly, each Instagram post collected by X1 is treated as an individual record in Relativity, instead of the bulk export from other tools being a single record. This enables efficient review as well as robust data analytics of social media evidence in Relativity.

To see all these exciting new features in X1 Social Discovery v7, please watch our product tour on-demand. Alternatively, we would welcome the opportunity to brief you and your colleagues directly. Please contact us to speak with a member of the X1 Team.

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April 18, 2023 · 10:49 AM

Social Media Evidence Proves Essential in Recent High-Stakes Trademark Infringement Matters

By John Patzakis

Recent court decisions reflect how social media evidence can play an important role in establishing actual confusion in a trademark infringement lawsuit. With the rise of social media, businesses and individuals have been able to reach wider audiences and create their own brand identities. However, this has also led to an increase in trademark infringement cases, as individuals and companies attempt to profit from the goodwill and reputation of established brands. In these cases, social media evidence is often instrumental in establishing whether there is actual confusion among consumers, which is a crucial element in proving trademark infringement. Social media evidence can help establish actual confusion by demonstrating how consumers interact with the marks in question.

In addition to user interactions such as comments or hashtags, social media evidence can also include analytics data and other metrics. For example, businesses can use social media analytics tools to track how consumers are interacting with their content and whether there are any spikes or changes in user behavior when a competitor begins using a similar mark. This data can help demonstrate actual confusion among consumers.

To establish trademark infringement, a plaintiff must prove that a defendant’s use of a mark is “likely to cause confusion” with the plaintiff’s mark under Title 15 of the U.S. Code, Section 1125(a)(1)(A). Many plaintiffs have recently highlighted social media posts, including hashtags, to establish evidence of actual confusion, which further bolsters their claims.

In Hermes International v. Rothschild, t (S.D.N.Y. Feb. 2, 2023), the luxury brand Hermès filed a trademark infringement action against the defendant who created and sold “MetaBirkin” nonfungible tokens (NFTs). Hermès asserted that Rothschild’s NFTs infringed upon its famous Birkin handbags both in name and appearance. Hermès successfully defeated a summary judgment motion by introducing social media posts into evidence that allegedly reflected actual confusion from consumers, including posts that read:

“Finally an NFT my wife can get on board with! Would LOVE to get her this Birken [sic] for Christmas!”

“I need this Birkin for the wifey! Please whitelist me sir. #WAGMI #MetaBirkins”

“Birkin NFT is the future of fashion.”

Hermès ultimately prevailed on their claims at trial based upon this and other key evidence.

In Great Western Air LLC v. Cirrus Design Corp., (D. Nev. Jan. 6, 2023), a personal airplane manufacturer, Cirrus Aircraft, asserted trademark infringement against a private charter jet company, Cirrus Aviation. Cirrus Aircraft sought at trial to establish actual confusion by pointing to various social media posts that showed images of Cirrus Aircraft planes, but tagged Cirrus Aviation’s social media handle, or that had hashtags such as #cirrusaviation.

But social media evidence reflecting evidence of actual confusion cannot help your case if it is not properly authenticated. In S10 Entertainment & Media LLC v. Samsung Electronics Co. Ltd., (C.D. Cal. Feb. 14, 2023) Samsung successfully objected to the admission of social media evidence that the plaintiff sought to admit into evidence. Specifically, Samsung successfully excluded what the court opinion describes as “21 unauthenticated social media posts and messages from Twitter and Instagram that S10 Entertainment purports indicate actual confusion” including “an unauthenticated YouTube video (and related screenshots).”

The court ruled that if the plaintiff intended to introduce social media posts from third parties to demonstrate that those third parties were confused, it could not authenticate those posts because it “cannot even demonstrate that these comments are real people.” The plaintiff’s use of screen shots and other failures to use best practices to authenticate the social media evidence was very costly, and defendant Samsung prevailed at trial one month after the pre-trial evidentiary hearing.

Litigants in trademark and other intellectual property actions should both understand the treasure trove of key evidence social media feeds provides, while at the same time employing best practices to properly collect and authenticate this critical evidence source.

X1 Social Discovery is the only eDiscovery solution to provide post-level parsing for social media posts, which is essential for both scalable collection and evidentiary authentication. To learn more about this important functionality, please contact us for more information.

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