Applied Linguistics at KMUTT

In his talk earlier this week, Hayo cited 8 types of data from Purdam and Elliot (2015 - see https://drive.google.com/file/d/0Bxa1ZO ... dKazA/view). These are:
1. Orthodox intentional data (e.g. surveys, interviews)
2. Participative intentional (e.g. crowdsourcing)
3. Consequential data (e.g. admin records)
4. Self-published (e.g. blogs)
5. Social media (e.g. Twitter)
6. Data traces (e.g. search histories)
7. Found data (e.g. observations)
8. Synthetic (e.g. simulations)

Numbers 2 and 3 strike me as particularly interesting, since they are rarely considered but could be done (I also think number 6 is interesting in the same way, but doubt that data could be collected).

Can anyone come up with interesting research projects that would use either crowdsourcing data or consequential data?

One example of "participative intentional" (or crowdsourcing) data that I have used in my own research is the Small World of Words database found at https://smallworldofwords.org. This website collects data from users around the world about word associations. Basically the way it works is that the website gives you a word and asks you to type in the words that come to your mind. So it might say "black" and that makes you think of "white" or "cat".

For the data type of "consequential data" one example could be actions and speech in a virtual environment such as Second Life or Minecraft. The data is not intentional like the example above because the subject is just playing the game and moving around and talking in order to accomplish some goal in the game. But this data could be used for research purposes that have nothing to do with in-game goals.

(By the way, if anyone is interested in reading further about these data types, the book that Aj. Hayo cited is available in the RC at RM 372.)

Most of us might be familiar with Project Implicit (https://implicit.harvard.edu/implicit/takeatest.html) and MinEd game (http://meg.ibankstory.com/index.php) which make use of the crowdsourced input.

Another example of crowdsourcing with social media is S-sence project by NECTEC (http://ssense.in.th/). (It’s in Thai.)
S-sence analyses posts on Twitter, Facebook, webboard, and other social media sources and reports positive or negative attitudes towards the topics, e.g. tourist attractions (http://ssense.in.th/tourism/). You can also search for a specific issue here (http://pop.ssense.in.th/index2.php). I think the idea of the project is interesting, but the developer has to think more seriously about choosing appropriate sources of information.