Sentence generation with choice-based typing. The program prompts a user to choose one of two words that are likely to come after the previous words, allowing them to generate a whole sentence by low-effort interaction.—programmed by Jeff Bigham
How small can a crowdsourcing contribution be?
At November’s CrowdCamp workshop, a group of us got together and prototyped a number of sample systems to see how low-effort crowdsourcing would work. We posted a report at Follow the Crowd.
Our prototypes were silly at times, but helped us think about the mixture of low-effort input methods and non-distracting user contexts where low-effort crowdsourcing would work.
The ideas we prototyped, available at Github, include:
- A binary tweeting interface, that lets you type sentences using a choice between common words
- A passive image voting interface that captures a user’s smile as a ‘like’
- A browser extension proof-of-concept that lets a worker complete tasks while a page is load
- A hot-or-not style interface for choosing the better of two choices. The twist is that you’re choosing using affirmative grunts, so you can play it while listening (or pretending to listen?) to somebody!
The emotive voting interface ‘likes’ an image if you smile while the image is on the screen, and ‘dislikes’ if you frown.
Details at Follow the Crowd. Team was Jeff Bigham, Kotaro Hara, Rajan Vaish, Haoqi Zhang, and myself.
Based on an XKCD comic, the Up-Goer Five text editor only lets you write using the one thousand most common words in English. Here are my attempts to describe what I do in crowdsourcing and information retrieval using only common words.
How do you find something from a lot of written stuff? If there are hundreds of things or more, you can’t look at all of them! One way we can find things is to use the words to understand the ideas. Then, when you search with a question, we can find the ideas that you are asking about and find the written things that answer your question. However, words and ideas aren’t exactly the same thing, so we look for ways to make better how a computer understands the ideas in your question and in the stuff you’re looking through.
When people get together on computers, they make fun, cool, and strange things. My job is to understand why they do it, and how we can can work together to fix problems in the same ways.
Click the image for a map of topics in the Day of Digital Humanities. This was a product of a failed method that I was working on. I meant to share this on Twitter, but compression made it look terrible.
I wrote a simple word count tool the other day. It adds a ‘word count’ option to the context menu (i.e. right-click menu) when you select text in Chrome. Install here.
A general purpose productivity tracker
I just published Progress Bar Timer in the Chrome Web Store. It lets you set up general purpose trackers in the form of progress bars. There are counters, timers, and clocks. Code is at Github, so feel free to submit bug reports and suggestions.
The application was designed toward my productivity habits but – spurred by the sense of the public eye on Github – I’ve tried to make it useful to others. My favorite use has been to combine a counter and a clock side-by-side. For example, during my field exam, I maintained a bar of word count progress alongside a bar showing where in the two week writing period I was.
In Historical Note: Information Retrieval and the Future of an Illusion (1988) Don Swanson offers his experienced perspective on IR and problems that we’ve ignored. He suggests that we explicate so-called ‘postulates of impotence’: statements of what cannot be done.
Swanson offers some postulates of impotence himself, as well as postulates of fertility. I like the idea of a research community formalizing the lies they’ve been telling themselves, so I’ve reproduced a truncated version of his postulates below.
In his postulates of impotence (PI), Swanson argues that fully automatic indexing and retrieval is not effectively possible. While he admits that computing brings many benefits or scale and speed, his PIs seek to remind us that it doesn’t necessarily mean that we are better at retrieval.
In his postulates of fertility (PF), Swanson offers a little-explored area where IR can help: making connections between disparate information that had not been considered previously. He cites scientific fields as a place where there is limited discussion and citation across field boundaries, but where doing so is extremely useful.
Do you have your own postulates of impotence for your field?
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