Social Mining Tools
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Steven Rosenbaum is a curator, author, filmmaker and entrepreneur. He is the CEO of Magnify.net , a real-time video curation engine for publishers, brands, and websites. His book Curation Nation is slated to be published this spring by McGrawHill Business. As the volume of content swirling around the web continues to grow, we're finding ourselves drowning in a deluge of data. Where is the relevant material?
The thing that amazes me most when it comes to what is supposedly "news and content curation" on platforms like Scoop.it, is that some of the most popular and trafficked channels have nothing to do with curating a topic for a specific audience. Why? Because if you look at the supposed "curation" done on these channels, it is nothing but simple and often very superficial picking and unrestrained sharing of links with absolutely no concern for checking, verifying or let alone reading what is being posted. This is how I long lost trust for many such curators. Because they are literally doing the opposite of what a true content curator should do: vet, verify, analyze, explore, check, add, inform, contextualize and reference.
Data Mining is the differentiator . Some have labeled the current period, appropriately, as “The Age of Analytics,” a period in which the information age has led us to the application of analytics to derive insights from these incredible sources of data. Testimonials "We have purchased STATISTICA Data Miner for our department under Higher Education Quality Enhancement Program (HEQEP) from Arc Bangladesh Ltd. On 12th and 13th of October 2012 StatSoft India in collaboration with Arc Bangladesh conducted two days onsite interactive training program... We found the training program very informative for our faculties and students."
Text Mining Introductory Overview The purpose of Text Mining is to process unstructured (textual) information, extract meaningful numeric indices from the text, and, thus, make the information contained in the text accessible to the various data mining (statistical and machine learning) algorithms. Information can be extracted to derive summaries for the words contained in the documents or to compute summaries for the documents based on the words contained in them.
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