Small Data on Social Media How to Leverage Information for Collective Use

Every day, we surround ourselves with data. We save Instagram posts with promising recipes, YouTube videos with book reviews, TikToks with movie recommendations, and bookmark threads on X to revisit later. However, this information often sits in our “saved for later” lists without ever being revisited, and even if we need it, it can be time-consuming to locate and relate it to other data.

The Power of Small Data

In a hyperconnected world, each social media user plays a crucial role in data generation. Some consume information and organize it for personal use, while others create relevant content on specific topics. What’s fascinating is that this small data, created and organized individually by people across the world, often remains fragmented and unavailable to the public, even though it could be of great value to those interested in accessing it.

This type of data, which is more localized and detailed, is what we call small data. Social media data is a prime example of small data—individual pieces of knowledge and experience shared from unique perspectives. From a bar review on Instagram to a recommendation thread on X, these pieces are “small” not only in volume but also because they capture moments, opinions, and personalized insights that may seem insignificant in isolation but gain substantial value when connected and contextualized with similar data.

The Value of Organizing Social Media Information

At Datasketch, we believe that small data—local, specific, and contextual—can have great collective value when properly organized. Through tables, we transform this scattered social media data into structured, accessible information, converting personal experiences into valuable resources for all.

Want to learn more about data cleaning and structuring? Check out our blog.

For example, during COP16 in Cali, a user on X started a collaborative thread inviting locals to share restaurant, tourist spot, and entertainment recommendations for visitors. The post was saved by 432 people, likely because they found the information useful for future reference or visits. Additionally, many joined the conversation, contributing their own recommendations in the thread.

While valuable, this information is scattered across different messages in the thread. By organizing these recommendations in a table with columns for location, description, and social media handles, the result is a practical, easy-to-use guide that any visitor could consult—even after COP16. In this way, personal experiences become a helpful tool for future travelers.

Using Datasketch, we organized all the information from the thread into a structured table. By doing so, we not only centralized the data but also unlocked new possibilities: others can create visualizations like maps of tourist spots, easily access the information, or keep enriching the database with additional contributions. This transforms a thread of scattered recommendations into a valuable, dynamic resource that also represents data that would otherwise be costly to collect through other means.

How Datasketch Turns Small Data into Collective Knowledge

Small data on social media goes beyond just posts; it also includes publicly shared user information like names, contact details, or countries of origin. In some cases, this information holds particular importance—especially for businesses that operate exclusively on social media and rely on visibility to reach customers. Instagram is filled with commercial accounts that users follow for future purchases but often forget about. When it’s time for a birthday, special event, or trying a new dining spot, users often go through endless searches for information they had already seen or saved.

By organizing this data into a table within Datasketch, we create a structured, accessible resource that lets users rediscover and explore available local businesses without relying on scattered searches. Structuring the data also allows us to add additional variables that may not always be explicitly published but can be inferred from descriptions or shared data, like a business’s location based on its address. This enhances local knowledge about what’s available in a neighborhood or area. Although it can be difficult and costly to gather this kind of information, it’s readily available on social media—but without organization, it often goes unnoticed and is not recognized as a valuable resource. Once information is consolidated in Datasketch, users can take various actions, such as creating visualizations or even developing websites based on a template. Imagine having a website containing everything you’ve saved on social media—that’s exactly what we did with social media stores. Visit the site here

There are countless examples of how user-generated data on social media can be transformed into valuable resources when gathered in one place. If you have saved threads with recommendations or collections of interesting posts, why not give them new life? Join the Datasketch community and start organizing the data you store on social media.

Sign up here to turn your small data into collective knowledge.