When it comes to deciphering hidden meanings and patterns within data sets, analytics surely come in handy. Companies leveraging Predictive Customer Intelligence are better off at tracking the social media endeavors of groups and individuals, thereby keeping residual threats at bay. Moreover, in this era of cut-throat competition, it is necessary to monitor the social media platforms, regardless of the business structure and size. That said, it is important to assess the existing and prospective threats in advance before moving ahead with a counterattacking plan.
Evaluating Social Media Threats
Social media threats help evaluate the criminal intent of concerned individuals. Be it an act of violence or a generic crisis, it is the responsibility of investigators to analyze the threats and mitigate the same with urgency. However, there are times when detecting issues becomes hard as the social platforms receive more than 500 million messages on a daily basis and there is way too much unstructured data to take care of. This is where analytics come in handy as they assist investigators and allow them to make the right call.
The Concept of Social Media Threat Analytics
When it comes to identifying online threats, social media threat analytics is a great tool to have. However, this option involves specialist expertise and advanced technology— making the implementations tougher than usual. That said, e-tradecraft is an evolved technique that functions better than social media threat analytics. E-tradecraft makes use of law enforcement and military experiences for detecting threats and potential dangers within a span of few minutes.
Although this tool comes equipped with advanced technologies, it lacks enough smartness to evaluate situational risk potential pertaining to the online content. Sentimental analysis is the underlining concept behind e-tradecraft but the subtlety seems to be missing. This analytical approach could only comprehend the words and associated sentiments— therefore missing out on several critical instances.
Harnessing Cognitive Analytics
We all must realize that every customer is different and each one has a different perception towards threats. Having Predictive Customer Intelligence at the helm allows organizations to identify unique user problems and come up with personalized solutions for the each. IBM’s Watson Analytics branches out of PCI and works in close proximity to the existing data sets— ingesting and analyzing unstructured bits for assessing threats. This form of Cognitive Analytics brings a lot of new things to the table— including the geographical threat monitor. In simplest of terms, PCI when combined with the concepts of Cognitive Analytics can surely work as a force multiplier; improving the chances of encountering and mitigating threats.
Safeguarding Communities and Clients
Now when we have established the bases pertaining to the implementation of PCI, Cognitive Analytics and Watson Analytics— all in coherence with each other, it is time to analyze the solution offered by the secured framework. To begin with, Predictive Analytics combined with necessary intuition accelerates data collection. The entire concept of threat avoidance is based on timeliness and having a prompt strategy surely comes in handy. Moreover, the faster we detect threats, greater are our chances of redemption.
The next solution revolves around social media coverage and the diverse set of analytics readily offers a sneak peek into the existing data sources. These insights can be combined with varied online sources and dark web inferences— precisely for activating an innovative security schema.
Lastly, these analytics allow us to gauge the actual context of a message regardless of how the words have been placed. Instead of being restricted by the sentiment dictionaries, PCI and Watson Analytics work in cohesion towards eliminating the false positives. This strategy also ensures that the actual threats aren’t neglected.
Safeguarding clients and customers from social media threats is something every organization must strive for. With truckloads of unstructured data available online, customers are prone to frequent security hazards. However, having Predictive Customer Intelligence in place— clubbed with Cognitive Analytics— can improve the chances of threat detection. While sentiment analytics can help organizations decipher the motivation behind a post, link analysis is an analytics-driven approach that comes equipped with locational inferences. This approach also helps detect individual connections, threat resources and even the concerned aptitude for creating chaos. At the end, it’s all about finding patterns and evading dangers associated with the same.