How Media Monitoring Technology Actually Works

Underneath the media monitoring tools is technology that has been developed to address the challenge of finding relevant information regarding a company in a sea of content that is constantly being generated by the millions of sources that exist.

Automated Content Discovery

The first step in media monitoring is the use of automated tools to monitor the content of various media sources, such as news sites, blogs, social media sites, forums, and review sites.

The tools used for media monitoring use the concept of web crawling and API integration. Crawlers use the internet as a resource to fetch the required data by downloading the required pages from the internet and then following the links to fetch more data. In response to this, the server will fetch the data from the API provider, then send the data back to the user in a raw format, usually a JSON or XML document.

Keyword Matching and Boolean Logic

After content is ingested, filters are used to pick out relevant mentions. The simple method involves keyword matching, looking for specific words such as company names, product names, or industry terms in the content flow.

More sophisticated methods use Boolean logic, enabling complex search criteria that include multiple keywords, eliminate irrelevant results, and factor in variations.

Natural Language Processing

Natural language processing is used in modern monitoring systems to analyze context beyond the presence of certain keywords. Sentiment analysis is the use of natural language processing and machine learning technologies to train computer software to analyze and interpret text in a manner similar to human analysis.

Sentiment analysis software utilizes machine learning, statistics, and natural language processing to automatically analyze the sentiment of large volumes of text, such as web pages, online news articles, internet discussion groups, online reviews, web blogs, and social media. The software analyzes the text surrounding the keywords to determine whether the keywords are mentioned in a positive, negative, or neutral context.

Alert and Reporting Systems

Media monitoring technology provides value to the user in two ways: alerts and reporting.

The alert systems are designed to notify teams when certain conditions are met, such as a sudden increase in the number of mentions, the presence of negative sentiment, or the presence of mentions in influential sources.

Reporting systems also combine all gathered mentions into a visual representation, enabling users to see patterns over a period. These reporting systems usually show such metrics as trends in mentions, sentiment, and source. For instance, Pulse Media Scout is a system that enables users to gather all mentions from different sources into a single reporting system. This means that users can analyze patterns from news sources, social media, blogs, and forums without having to compile data manually.

The Human Factor

Even the most sophisticated AI-powered sentiment analysis and social media monitoring software must have human input to ensure consistency and accuracy of analysis. The nuances of meaning depend on human interpretation. New slang is a problem for language models. Niche sources may not be detected by automated tools.

The best monitoring solution combines the efficiency of technology with the expertise of human analysts—leveraging technology to point to important content and using human expertise to interpret meaning, determine significance, and suggest an appropriate course of action.