Introducing Nielsen Buzzmetrics Research- The Global Measurement Standard in Consumer Generated Media

Date

August 11, 2006

Speaker

Navot Akiva

Affiliation

Nielsen Buzzmetrics

Overview

When we talk about analyzing vast amounts of consumer-generated media in order to find the “gold” in specific topics, issues, trends, opinions and sentiment, we’re talking about some powerful technologies that do the heavy lifting.

Nielsen BuzzMetrics’ content mining capabilities are rooted in machine-learning and natural language processing technologies that mine unstructured data—vast amounts of raw text—to discover the intelligence it contains. These technologies are able to identify key phrases and words, detect the nature and strength of sentiment in text, classify and categorize data to provide meaning and relevance, and extract specific facts and data points to create the meaning and context that lead to intelligence.

Nielsen BuzzMetrics (NBM) technology can be trained to identify and analyze relevant messages about your brand, products and company from a variety of online external and internal sources. In addition to measuring the sheer volume of buzz, specific technologies include: Relevance Detection, Classification, Phrase Mining, Sentiment Mining, Quote Mining, Concept Mining, Social Network Analysis, Fact Extraction Dispersion and Link Analysis.

In this talk we will introduce NBM research motivation and technology as well as several use cases of how some existing clients benefit from using our technology.

Speakers

Navot Akiva

Navot Akiva M.Sc. M.B.A. is a research scientist at Nielsen Buzzmetrics, specializing in style based text categorization and text mining technologies.