Majority of the crimes today are form social media and most of the crimes are preconceived and disseminated.
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Social media has become one of the major data source for quantitative communication research over the past decade. In addition to survey, experiment, and content analysis, social media harvesting is the fourth primary method of data collection in social sciences. The increasing social media use has generated rich information online that is archived instantly on web servers. Although much of this information is open very useful, it is rarely in a form researchers can use directly.
Our Open Source Intelligence (OSINT) Tool “Social Wide area Network Analytical Tool” (SWANT) is an intelligence gathering system that offers end to end services (both hardware and software services) to mine immense data from publicly accessible web source such as social media (Facebook, Instagram, Twitter, Google, YouTube etc.), blogs, forums, news publications, wikis, chat rooms and others. The gathered information is exploited and disseminated by automatic analysis and manual processing to address a specific intelligence requirement of the client.
From counter terrorism, cyber security, anti-money laundering and fraud protection, to network intrusions and malware attacks, private and government organization must be able to protect against a threat landscape that is both asymmetrical and increasingly sophisticated. Our OSINT software rapidly processes high volume and multi-source information by assigning meaning and context to processing unstructured datasets. Extracting entities and their relationships and normalizing names into text for accurate identification, analysis and synthesis of information.
Our SWANT tool is custom made for the intelligence community, supporting Governmental Intelligence, Law Enforcement Agencies and Corporate Security customers in accessing, processing and synthesizing information. It will rapidly processes high volume and multi-source information by assigning meaning and context to processing unstructured datasets, extracting entities and their relationships and normalizing names into text for accurate identification, analysis and synthesis of information.