Abstract: The researchers combined two lists of 28 favorite “data science experts to follow on Twitter” to seed a Twitter network and analyze whether the recommended experts were indeed amongst the most influential “data science experts” on Twitter. They analyzed the resulting Twitter network to find the most important nodes in terms of popularity, quality of connections, types of roles played, such as bridges, and node ability to quickly spread information. They found that only some of the recommended experts appeared most influential given the ...
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Topics: 
Data science
World Wide Web