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.

The first API I used was the Covid Data API. For our last project we used an API that gave us words for Hangman. We also a jokes API. Currently we are using an API to give a recipe for our suggester.

  • 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?

The biggest discovery I found was that you can have a website on github pages, and set up actions so that what you commit will autonomously deploy on github pages.

  • 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?

They have lots of different categories and a vast variety of databases.

Hacks

Think of a use case for crowdsourcing in you project …

  • CompSci has 150ish principles students. Describe a crowdsource idea and how you might initiate it in our environment?
    Our slack channel is basically an example of crowd sourcing, as we have a large group of people who can help if we ever run into any difficulties.
  • What about Del Norte crowdsourcing? Could your project be better with crowdsourcing? Yes, our project would definitely improve with crowd sourcing. Because we are going to have a feature where users can add reviews on recipes, the more reviews we have will definitely make our website seem more reliable.
  • What kind of data could you capture at N@tM to make evening interesting? Perhaps use this data to impress Teachers during finals week. As said earlier, the more reviews we have, the more impressive and interesting our project will be. So on the day of N@TM we would be looking to get users to not only use our recipe suggester but to also leave reviews for each recipe in order to better our product.