The Historise Social Monitoring system analyzes millions of social media posts and news publications around the world to predict the behavior of Internet users, and calculate their future interest in a particular topic. It provides the most complete picture of brand, person, and company mentions in social media with subsequent in-depth analysis of the data in real time. The expert system is able to identify weaknesses in the brand’s online reputation and make recommendations for improvement.
Incoming data is enhanced by attaching valuable metadata such as age, gender, and location of the author. Rosette Language Identifier detects the language of each item for linguistically appropriate enrichment and processing to make Historise’s search with Elasticsearch and Apache Nutch yet more accurate and comprehensive. With Rosette Entity Extractor, Historise also pulls out names of products, companies, and people, and can then deduce high-level topics (e.g. sports, banking). Rosette enables Historise to enrich social media content in its native language, thus recognizing the mention of a brand or person across many languages. And spelling variations, errors, nicknames, and other name variations are smoothed out with Rosette Name Indexer, ensuring that “Chas. Schwab” will be matched to “Charles Schwab.”
“We have developed the Historise Social Media Monitoring System for companies to better understand how consumers relate to their product and gain insight into how to improve the quality of their goods or services,” said Dmitry Baykov, CEO Historise Ltd. “Basis Technology and its proven Rosette platform enable us to provide customers with the most comprehensive analysis of the opinions and mentions of a product, person or company on the Internet across many languages.”