Social Media Intelligence and Data Mining: what is the relationship?

Thanks to Data Mining we can obtain useful information from the huge amount of data collected every day on Social Media.

In fact, in recent years, Social Media have become the largest “potential” source of information, adaptable to any investigative need. By way of example, we mention some sectors: commercial, journalistic, social, judicial investigation, public safety, etc.

Why “potential”?

Information can only be collected if there is structured data at the base of which we are able to understand the relationship between them. However, on the web, most of the data is unstructured and unusable.

In a previous article we explained how Sentiment Analysis software takes unstructured data from the web and structures and classifies it so that the machine is able to return useful information about users’ emotions, preferences and ideas. In this we will dig into the digital mine even deeper to discover Data Mining.

What is Data Mining?

Data Mining is the set of techniques and methodologies that allow the extrapolation and analysis of large amounts of data. To do this we use machine learning, artificial intelligence, statistics and databases methods.

Data Mining is typically preceded by other stages of data preparation and filtering such as Data Cleansing. Once you have clean data, Data Mining is able to identify relationships, anomalies and recurring patterns from which to draw valuable information.

The basics of Social Media Intelligence

Social Media Intelligence (SMI) is defined as the set of operational activities aimed at obtaining useful information through the extraction and analysis of data from social media.

As we have already pointed out in the introduction, it is not an easy operation to extrapolate information from large amounts of unstructured data. Moreover, if we were to rely only on human work, such an undertaking would be really complicated and would take a very long time. It is for this reason that SMI relies on technologies such as Data Mining.

Data Mining and Social Media Intelligence: between contents and relationships

The nature of Social Media is made up of two fundamental elements:

• Contents (posts, articles, comments, images, videos)
• Relationships

This is why SMI has concentrated on studying Data Mining processes on these two fronts. In the first case it gave rise to semantic engines capable of analyzing large strings of data and obtaining information also thanks to Natural Language Processing (NLP). Just to give an example, let’s think of the well-known Sentiment Analysis. In the second case, Data Mining is used to understand the relationship between users and / or content on the web.

We therefore understand that, thanks to social media, we have at our disposal a potentially infinite mine of data that can be transformed into precious jewels. But this will only be possible if we recognize the importance of tools, such as Data Mining, to dig deep.

The solutions of Pragma Etimos

We develop structured and classified data models (Intelligence Data Table) resulting from years of innovation in the semantic field and we use them as a basis for the construction of neuronal models, territorial links and semantic analyzes. We thus obtain information from unstructured data, creating relationships and classifying them so that they can be reused in an analytical and strategic way.

Advantages:

• Quality actionable data
• Enriched database
• Strategies based on consistent and comprehensive data analysis
• Reduce time and costs

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