DataSift brings machine learning to analyzing social data
Information from social media is becoming more and more important to many companies. But extracting data and getting something useful from it can prove difficult.
Business intelligence specialist DataSift is launching a new technology called VEDO Intent, which aims to take social analysis further, gaining more nuanced insights into markets and customers using machine learning.
Previously this sort of analysis would have always relied on human input, but by using an approach known as Active Learning, VEDO Intent learns as posts are manually classified into categories such as rant, rave, purchase intent or churn. VEDO Intent then dynamically builds a machine learning-based model to at first suggest, and then fully automate, the real-time classification of millions of posts to uncover insights that previously would have been hidden. By having a system carry out the data analysis it also helps protect individuals' privacy.
"Organizations have long recognized the huge potential of social data -- it's the voice of the market and the voice of your customer. Companies are now hungry to go beyond sentiment analysis into more advanced insights," says Tim Barker, Chief Product Officer at DataSift. "Social data has evolved. Everyone from financial institutions through to the United Nations refers to it and we recognized that people need actionable, nuanced insights from social data to better understand their audience’s mood and intent".
The company is also launching a forum to help developers and data scientists share statistical models that form the building blocks of advanced analysis. Helping guide researches to the keywords and hashtags they should be using in their analysis for example.
More information about VEDO Intent and the forum can be found on the DataSift website.
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