Category Archives: Crowdsourcing

SiSense: Scaling Users, Not Data

In a new Saturday Night Live sketch, “Secretary Sebelius” explains that is so slow because it was designed to handle only six users at a time. We’ve become accustomed to everything online slowing down with additional users, but SiSense last week announced the … Continue reading

Posted in Big Data Analytics, Crowdsourcing, Interviews, Machine Learning, startups | Leave a comment

The OED, Big Data, and Crowdsourcing

The term “big data” was included in the most recent quarterly online update of the Oxford English Dictionary (OED). So now we have a most authoritative definition of what recently became big news: “data of a very large size, typically to the extent that its … Continue reading

Posted in Big Data Analytics, Big Data History, Crowdsourcing, Data Science | 2 Comments

Revisiting Big Data and Crowdsourcing: Kaggle Today

I launched this blog a year ago in June 2011. In one of my first posts, I discussed “Crowdsourcing and Big Data,” offering a typology of crowdsourcing and connecting it to big data by mentioning a little-known (at the time) … Continue reading

Posted in Big Data Analytics, Competitions, Crowdsourcing, Kaggle, Predictive analytics | Leave a comment

12 Rules for Managing Crowdsourcing Communities

Tonight at Crowdsortium Boston II, I heard the following advice: Remember that the crowd is what you acquire from, not what you sell to. Don’t try to replicate your best user (otherwise, all users will look the same). Win over … Continue reading

Posted in Crowdly, Crowdsourcing, Libboo, onForce | Leave a comment

Google Plus Zagat Equal Google Channels

If content is king, content brands are emperors. Zagat is the inventor of content crowdsourcing (in 1979!) and the emperor of crowdsourced (and edited!) local reviews. For Google, this is yet another step in expanding its content ownership and the … Continue reading

Posted in Crowdsourcing, Google, Information Business | Leave a comment

Crowdsourcing and Big Data

The Wikipedia article on Big Data says it “requires exceptional technologies to efficiently process large quantities of data within tolerable elapsed times.” The examples given (Hadoop, MapReduce, Cloud Computing, etc.) do not include one very exceptional technology, the human brain, … Continue reading

Posted in Appswell, Business Impact, Crowdsourcing, Data Scientists, Innocentive, Kaggle, uTest | 8 Comments