Data Science: Ranking Online Influencers
Data science is the defining specialty of the business of big data and an emerging career path for those who love to find new insights in the gazillion bytes of data created each day.
Data science is the defining specialty of the business of big data and an emerging career path for those who love to find new insights in the gazillion bytes of data created each day. It’s where you find fierce competition for talent, the jobs of the future, new training programs and courses, new ventures, and new products. But where to find the data science-relevant online conversations with the most impact?
With the Web as a worldwide publishing platform accessible to two billion potential creators and consumers of content, excitement generates lots of information overload. Traackr is one of a handful of companies that are trying to give us useful filters and guide us to the experts and influencers on specific topics. Traackr scours the Web to find the influential writers online using its three macro metrics: Reach, the size of an influencer’s audience; Resonance, the activity generated by an influencer’s audience; and Relevance, which matches the influencer’s online activity with a specified list of keywords.
Who are today’s influencers on the hot topic of data science? Take a look at the data science “A-List” I created with Traackr’s help, a dynamic ranking of the influencers that bring us news and analysis about the tools, ventures, and accomplishments of the new breed of data scientists.
But who are these data scientists, you may ask? Almost all the people on the Traackr data science list write about data science but do not practice it. They are great guides to not only what is new in data science but also to those data scientists that emerge from time to time from underneath the data to speak publicly about what makes them tick.
Last week I published on AllAnalytics.com short profiles of nine data scientists, public figures I randomly selected to represent the new species of data scientists. As often happens when a new discipline or job category emerges, we find a wide variety of expertise and experiences in the shaping of the new men and women of data science.
Here’s to the doers and to the writers who tell us about their good deeds!
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