Crowdsourcing

The more you crowdsource, the more you reach beyond your own community, the more likely you will reduce Computer Bias. Crowdsourcing provides the ability to obtain shared information, share information, and participate in distributed computing.

Evidence of Crowdsourcing

  • Wikipedia has a ton of information from crowdsourcing, see Wikipedia definition on crowdsourcing. It can have inaccuracies, but when it does it often is corrected through a self-policing community. Reviews and many authors have made this, according to many, better than “official” information.
  • Crypto currency and associated block chain. All exchanges of money are validated at least 3-times by independent miners. If there is a flaw in the independent calculations the process is checked and performed again. Innovation of crypto crowdsourcing has impact on how governments think about currency. Additionally, block chain algorithms are being considered for many other crowdsourcing most private data (ie medical records).
  • COVID data, it is easy to recognize areas that are contributing and not contributing. This data has impacted all our lives and decision we make on attending public events, flying on planes, or wearing masks. The community of data and analysts will spawn many new ways of thinking about data that impacts lives.

Obtaining Data via Crowdsourcing (Crossover Group Up, ~10 minutes)

  • We have all experienced Crowdsourcing by using external data through API’s, namely RapidAPI. This data has influenced how we code and shown possibilities in obtaining and analyzing data. Discuss APIs you have used.

Last trimester, my team used an API which contained a list of words for our dictionary project.

  • We have all participated in code Crowdsourcing by using GitHub. Many of you have forked from the Teacher repository, or exchanged code with fellow students. Not only can we analyze GitHub code, but we can obtain profiles and history about the persons coding history. What is the biggest discovery you have found in GitHub?

One time I found code on Github which allowed us to make a 1 day timer which could detect when the day had ended. This was also used in our project from last year

  • Kaggle datasets for code and science exploration. The avenue of data points us youtube or netflix channels. Analyzing crowd data helps us make decisions. Exam top 10 to 20. Did you see anything interesting?

I saw a database for executions in the US. There were also a lot of databases for things like movies, social media, COVID, and other stuff.

Hacks

Think of a use case for crowdsourcing in you project …

  • CompSci has 150 ish principles students. Describe a crowdsource idea and how you might initiate it in our environment?

Night at the Museum is a great opportunity for crowdsourcing, since many people walk around to look at different projects. These people include families as well, so its not just one age group of people. Another idea would be to have people test the project similar to how Stats students went to different classes to collect data

  • What about Del Norte crowdsourcing? Could your project be better with crowdsourcing?

Our project could benefit from crowdsourcing by fixing the timer to include more time, based on how long people take to complete the puzzle on average. Another feature improved by crowdsourcing could be picking more recognizable logos for the cards in the card matching game.

  • What kind of data could you capture at N@tM to make evening interesting? Perhaps use this data to impress Teachers during finals week.

Some data we could capture is how long people stay interested in our game. We can use that to determine how long our game should run for. We may even add different options for how long the game runs for that the user can pick from.