Posts Tagged ‘Parse.ly’

Parse.ly Introduces Sponsored Content Performance Reports

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ATLANTA, GA–(Marketwired – Oct 17, 2013) – Parse.ly, the content performance authority [see our past coverage], today announced a feature to quantify the results of sponsored content and native advertising for publishers. Parse.ly is a content analytics and optimization platform that transforms real-time traffic, historical performance, social interactions, and global trends into actionable insights. This new capability gives publishers the added advantage of understanding and managing valuable paid content, and communicating its performance to brands via shareable, single-click, real-time performance reports. Read more

Election 2012: The Semantic Recap

There’s no such thing as too much post-election coverage, is there? Alright, maybe there is. But we couldn’t let things die down without at least a nod to those in our space that have delivered the semantic industry’s own take on the topic.

Here are a few you may want to review:

Twitris Election Insights:

“The Twitris system had an amazing night–while Nate Silver’s model might have received well deserved attention, Twitris gave better indications and insights and large majority of the polls,” wrote Dr. Amit Sheth, Kno.e.sis Ohio Center of Excellence in Knowledge-enabled Computing director and LexisNexis Ohio Eminent Scholar, in an email to us. The semantic social web application (first covered here) is a project of Kno.e.sis at Wright State University.

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Parse.ly Brings A Dash of Semantics To Online Publishers

Online publishers and other content providers have a new analytics tool to help them understand what their readers care about and use that information to better connect them to their sites’ relevant and compelling content. Launching today is Dash, based on the predictive content analytics platform Parse.ly. The technology crawls every article page for Parse.ly’s publisher-partners, and analyzes, in real time and at scale, the text to identify relevant topics to group related content together. Behind this lies natural language processing technology, which uses language queues hidden inside the text to determine its affiliated topics. To date Dash has extracted over 350,000 unique topics through all the URLs is has crawled during private beta for a healthy taxonomy of topics across the web being consumed by users.

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