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Why Web Intelligence is Crucial for All Kinds of Decision-Makers

May 31, 2021

Policy decision-makers, on-the-ground first responders, security forces, and epidemiological research teams need to manage, mitigate, and prevent emergency events. To make informed decisions, they need to know all the facts, ideally in real-time. In some cases, such as during a natural disaster, conventional modes of communication are often destroyed, which makes rescue operations or planning evacuations problematic. On the bright side, people use the internet and social media to document an event, inform people about their whereabouts, announce what they are planning or where they are going to be safe, and reach out to other people and groups. All this online information is a rich source for web intelligence that can be used to make informed decisions about what to do.
This means that these decision-makers need to gather relevant data from a wide range of online sources, especially publicly accessible sources such as OSINT websites. But analyzing relevant OSINT data harvested from the surface, deep, and dark web not only requires substantial resources and manpower but is also time-consuming, which could be critical in some instances, such as an earthquake.

That’s why they are looking for a comprehensive solution to prevent threats to public safety, protect the general population from events that could endanger their safety, and assist in case of e.g., natural disasters. But to be effective, they need a web intelligence tool. Such a web intelligence solution must be able to collect, analyze, and understand huge amounts of unstructured big data gathered from publicly accessible online sources using open source intelligence gathering techniques to gain real-time situational awareness.

At the web intelligence center, a query with relevant keywords and phrases is entered into the web intelligence tool, and the web intelligence platform (such as one of Cobwebs technologies) will display the collected and analyzed data in a GUI. This way, government agencies, crisis centers, and research teams are provided with real-time information based on geographic data, which helps them to e.g., identify where people had been trapped or stranded in case of a natural disaster and need to be rescued or evacuated. Effective web intelligence solutions must be AI-powered and leverage machine-learning (ML) and Natural Language Programing (NLP) algorithms to make sense of the vast amounts of information collected and analyzed from the web. They must also have geofencing capabilities to delineate relevant locations and keywords associated with e.g., a natural disaster. In general, location-based intelligence is the visualization and analysis of geospatial data to get situational awareness. This is important to generate alerts and handle the multitude of requests asking for urgent assistance based on the analyzed big data collected from open online sources on the surface, deep, and dark web such as forums, blogs, and message boards. In short, using a solution with a powerful WEBINT engine significantly improves the efficiency of providing assistance to impacted people.

Natural disasters, as briefly mentioned above, is just one of the many recent web intelligence case studies that were published to showcase the effectiveness of web Intelligence for making informed decisions. For instance, organizations from startups and corporations to government agencies use WEBINT tools to aggregate and analyze vast amounts of online data to get the insights they need to make data-driven decisions based on e.g., communications, trending discussions, and events.

WEBINT is not only crucial for protective intelligence but also for security intelligence, such as potential terrorist attacks, human trafficking, drug rings, and social media cyber security threats. For instance, national security agencies use WEBINT to stay abreast of national and global threats to prevent mass e.g., attacks aimed at governments and nationals, and law enforcement uses it to leverage their criminal activities by extracting crucial insights from web data to solve and prevent crimes.

To summarize, since the data extraction process is tedious and time-consuming, but critical to get insights for timely follow-up, all kinds of decision-makers, from on-the-ground first responders and epidemiological research teams to security forces and law enforcement, Web Intelligence is a must.



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