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The Pitfalls of Open Source Research 2024

Open source research is both a powerful and accessible tool for understanding global events. However, it’s not without its challenges. Even seasoned researchers can fall into common traps. Let’s delve into the seven common mistakes that can undermine the credibility and effectiveness of open-source investigation.

More people are turning to open-source research to make sense of the flood of information during major events. This method is increasingly seen as reliable. However, with great exposure comes greater scrutiny.


Whether you’re new to this field or a seasoned pro, being aware of these pitfalls can make a huge difference.

Not Providing the Original Source

The main tenet of open-source research is that it’s ‘open,’ meaning the information is publicly accessible and used transparently. This allows anyone to verify the sourcing and veracity of a piece of footage without having to trust the person who posted it. Without the original source, verification becomes much more difficult.

For instance, during Russia’s full-scale invasion of Ukraine in 2022, many “OSINT aggregator” accounts on Twitter posted videos from Telegram without linking to the original source. This lack of linking stripped potentially crucial information about the content. While social media platforms often remove metadata, platforms like Telegram retain it, which can be invaluable for investigations.

Letting Cheerleading Undermine Your Open Source Research Work

Bias is universal, but open-source researchers must attempt to separate their biases from the evidence they examine. Many researchers use these techniques to support a specific cause, but it is essential to acknowledge when sources or research do not support the cause and to be transparent about the level of uncertainty.

Confirmation bias leads us to accept information that confirms what we already believe and reject information that contradicts our beliefs. This can compromise the quality of open-source research. Therefore, it is important to acknowledge what you don’t know and be transparent about the level of uncertainty in your findings.

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Not Archiving Material

Online content can be fleeting, making the job of open-source researchers more difficult. Websites can go offline, links can break, and social media posts can be deleted. This is why archiving online content is so important. Third-party archiving platforms like the Internet Archive’s Wayback Machine are essential tools for this purpose.

Sometimes, these archiving tools fail to capture content from social media platforms or videos, making screenshots a useful backup. Archiving ensures that even if the original content is removed, a record still exists for analysis. Bellingcat frequently emphasizes the importance of this practice.

When content is not archived, valuable information might be lost forever. This is especially critical in investigations where each piece of data can contribute to the overall narrative. The lack of archived materials can severely hinder the process of verifying information and understanding events accurately.

Lacking Context for Occurrences, Common or Otherwise

Events can be misunderstood if taken out of context, especially in conflict monitoring.

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Researchers unfamiliar with specific data might misinterpret regular, planned events as something more significant. For example, controlled fires shown on NASA FIRMS images could be mistakenly seen as malicious activities.

In another example, a private flight from Anaheim to Toronto was mistakenly linked to baseball player Shohei Ohtani, even though it was unrelated. Such errors highlight the need for domain-specific expertise to distinguish between ordinary and extraordinary events.

Incorrectly Using Open Source Research Tools and Interpreting Data

Open source research tools require guidance, experience, and training to master. New users often overlook the limitations of these tools, which can lead to incorrect conclusions. For example, facial recognition software has its limitations and should not be treated with complete certainty without additional data points.

Tools that detect photo manipulation are another example.

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Misuse of these open source research tools can result in overconfident and incorrect conclusions. Proper training and experience are crucial to accurately interpret the data these tools generate.

For instance, drone footage of a fast-moving object may be mistaken for a UFO when it could just be a balloon. Similarly, clouds on satellite imagery have been misidentified as craters. These errors underline the importance of understanding the limitations and proper use of open-source tools.

Editing Footage

Editing footage can sometimes obscure crucial information. For example, overlaying audio tracks, creating compilations, or adding watermarks can make verification and analysis more difficult. Such practices often hinder the process of understanding and verifying the content accurately.

For instance, a watermark over a video frame can interfere with reverse image searches, a valuable technique for finding the origin of footage. Editing that obscures or alters vital information can compromise the integrity of the content, making it harder to investigate effectively.

Racing to be First at Any Cost

During breaking news events, the rush to be first can lead to mistakes. Social media platforms incentivize speed, but this can result in erroneous conclusions. High-profile misidentifications, like those during the Boston Marathon bombings and the Allen, Texas mall shooting, highlight the dangers of prioritizing speed over accuracy.

Verification should always take priority over being first. The desire for quick recognition can create more harm and confusion, rather than providing the facts needed to understand unfolding events. Accurate validation is essential for responsible open-source research.

Open source research is undeniably powerful but fraught with significant pitfalls. By avoiding common mistakes like failing to provide original sources and letting biases cloud judgment, researchers can maintain the credibility of their findings.

Archive materials diligently, and always strive for context and accurate data interpretation. Open-source tools should be used wisely and ethically. These principles are essential to foster trust and reliability in open-source investigations.

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Source: BellingcatTwitter

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