What Wikipedia Can’t Tell You About Media Monitoring

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Amazingly, a whole lot of people still think news tracking and media monitoring is a boring job where analysts pore through piles of newspapers highlighting paragraphs of interest to one or another client. Well, you still have some paperwork and human-made research in media monitoring. Machines and algorithms do the bulk part of the work, however.

How It All Began

It was in the late 1970s and early 1980s when intelligence agencies across the world started piling pieces of unstructured data and entering it into mainframe computers. The idea was simple – you put all the data you have into a machine and then a search algorithm is trying to find dependencies and interconnections.

It worked. It worked because this simple idea reflects how our society and business is working. A global world is connected in many ways and each piece of information matters. A company mention in an obscure media source may trigger reactions across the world. Information in one database or on a social media channel may prove business-critical.

News Tracking Is Not Just About Tracking

Hence, news tracking and media monitoring is not about following trends. This is part of the job but just a small part. Data drives the modern world to an extent a few people can imagine. You cannot be successful without ability to track data and track it smart.

And you need not be an intelligence agency to utilize the advantages provided by machine learning and artificial intelligence. We call it business intelligence and it is a core activity for any business aiming to stay ahead of the competitors. Business intelligence is based on information you have about competing products and services as well as mentions about your business across a variety of news channels.

Algorithms You Need

So news tracking needs algorithms that can pull out the required information searching through thousands of news sources, blogs, forums, and corporate web pages. This cannot be done by just tracking the news. You must apply an intelligent algorithm where focus words and extended keywords are incorporated to get valuable insights. You need algorithms that are able to track the market sentiment i.e. to extract emotional meanings in context. And no person can handle the tasks with a pen and paper, bearing in mind that news sources are virtually unlimited in a society where everyone has access to online space to share his or her opinion.

Actually, a good news tracking algorithm has nothing to do with simple “tracking”. You can write a program to track news sources in the comfort of your home. It is about generating insights using a media monitoring tool that is able to extract meaning from the noise generated on a variety of channels. In addition, such an algorithm should have machine learning capabilities to adapt to ever changing requirements and environment where company or product mentions may occur on quite unexpected media.

A Broader Look At News Tracking

You can find lots of articles and blog posts about media monitoring and some of them are worth reading. What you cannot find in popular online resources such as Wikipedia is dissection of the very core of a media monitoring service. There you will not find bureaucrats snooping at popular media but tech-minded people who try to figure out a method to both track and analyze media sources.

Finally, you can tell whether a news tracking service is worth trying if it offers insights, not plain monitoring. A good number of businesses have failed into the trap of using a “monitoring” service. Monitoring is the easy part of the job, what you are not told is that creating an algorithm able to generate insights is actually the hard task in any news-tracking endeavor.

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