Crowdsourcing – Improving Digital Humanities

With access to large amounts of data, coupled with large processing capabilities, capturing the wisdom of the crowds is now a resource that we have not had before. Whether it be using crowdsourcing as an alternative to hard evidence, in cases such as determining future stock prices, gathering large amounts of people to work on the same project, crowdsourcing, has many uses. Digital Humanities has already found a couple uses for the newly emerging tool.
Whether it be reddit, tumblr, flickr, or wordpress, whenever a user makes a text or image post, they post unique, “user-generated” tags. These tags are uniquely generated and self-influenced. Last class we touched upon the issue that although massive amounts of data is being uploaded everyday to the internet, there is very little preservation and organization being done to ensure that all information is kept safe. User-generated tags, on the hand, provide a way in which to find this data both more accurately, easily, and quickly, than from traditional.
According to a study by digital, “Data analysis revealed that participants in the [crowd-sourcing] and controlled vocabulary search condition were, on average, six times faster to search for each image (M = 25.08 secs) compared to participants searching with access only to controlled vocabulary metadata (M = 154.1 secs).” When the study was repeated multiple times, similar results were found.
Although tags generated by users are independent of any regulation, participant-provided tags are judged to be accurate 88% of the time, and there is no pattern differing tags of professional librarians from participants outside of the documentation field. This means that, as long as tags remains prevalent, much of the data provided on the internet won’t be lost, but, on the contrary, more accessible than ever! So all of those meaningless buzzfeed articles on “72 reasons why Honors391A is like breakfast” will forever be able to be found!
Google has recently implemented a “game” that allows users to add tags to otherwise untagged thumbnail images, allowing themselves to make sure that previously un-tagged images don’t get lost in the mix. They also crowd-source translation improvements, location guides, and improving google street-view.
Crowdsourcing has another use in digital humanities besides easily and accurately assessing data. When resources seem exhausted, images are often posted to the internet to find information otherwise unknown about it, whether it be location, people’s identities, or dates of when it was taken. Crowdsourcing is also implemented to colorize pictures, peice together maps, and even asking users to upload images of the same location, taken over different periods of time, to help map changes in the environment.
Crowdsourcing is useful in both reclaiming past digital humanities, improving already preserved digital humanities, and improving the processing of accessing them quickly and easily.

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