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Seth Grimes is an analytics strategy consultant at Alta Plana Corporation, located near Washington DC. Seth is also a leading industry observer, focusing on business intelligence, text and content analytics, and decision support systems. He is a long-time InformationWeek contributing editor and founding chair of the Sentiment Analysis Symposium and the Text Analytics Summit conferences.
I'm a heavy LinkedIn user, and I find the platform disappointing in so many ways. There are too many missing features surrounding the inability of the user to shape her/his own LinkedIn experience, so I really appreciate what you've written here. Thanks! For my own views on LinkedIn short-comings, check out, for instance, My Search for Relevance on LinkedIn and LinkedIn Misconnects Show that Automated Matching is Hard.
Janet, there's a lot of value in your guidance, but I can't help thinking, it's "content analytics that ignores the content." It's like analyzing, say, Paul Ryan's speech at the Republican convention by studying how long he spoke and how much applause he got, how many tweets and online articles, how many column inches of press... without regard to what what drove the numbers, his actual words and themes and, in the case of Ryan's speech, the analyses that saw the false, misleading, and exaggerated claims.
Hmm... I should blog this thought. We'll see.
Ian, I'm looking forward to application of the tools to the Text Mining group!
RainMakerMaker, thanks for your comment. As you've understood, I think, my own focus is on accounts that have been set up for the sole purpose of posting a flood of solicitations to groups. The situation, when bona fide LinkedIn users post in ways others challenge, is more nuanced and also, I'll add not something that LinkedIn could detect via data mining and deal with when a group's managers don't.