Phil 3.7.16

VTX 8:00 – 5:00

  • Continuing A Survey on Assessment and Ranking Methodologies for User-Generated Content on the Web. Also, Wayne found a very interesting paper at CSCW: On the Wisdom of Experts vs. Crowds : Discovering Trustworthy Topical News in Microblogs. Looks like they are able to match against known experts. System trust plus expert trust? Will read in detail later.
  • I’ve been trying to simplify the concept of information bubbles and star patterns, particularly based on the Sweden and Gezi/Egypt papers, and I started thinking about getting lost in a car as a simple model. A car or other shared vehicle is interesting because it’s not possible to leave when it’s moving, and it’s rarely practical to leave anywhere other than the start and destination.
  • For case 1, imagine that you are in a car with a passenger driving somewhere that you both know, like a commute to work. There is no discussion of the route unless something unusual happens.Both participants look out over the road and see things that they recognise so the confidence that they are where they should be is high. The external world reinforces their internal model.
  • For case 2, imagine that two people are driving to a location where there is some knowledge of the area, but one person believes that they are lost and one person believes that they are not. My intuition is that this can lead to polarizing arguments, where each party points to things that they think that they know and use it to support their point.
  • In case 3, both people are lost. At this point, external information has to be trusted and used. They could ask for directions, get a map, etc. These sources have to be trusted, but they may not be trustworthy. Credibility cues help determine who gets asked. As a cyclist, I get asked for directions all the time, because people assume me to be local. I have also been the second or third person asked by someone who is lost. They are generally frustrated and anxious. And if I am in an area I know, and speak with authority, the relief I see is palpable.
  • Case 4 is a bit different and assumes the presence of an expert. It could be a GPS or a navigator, such as is used in motorsports like the WRC. Here, trust in the expert is very high. So much so that misplaced trust in GPS has lead to death. In this case, the view out the window is less important than the expert. The tendency to follow and ignore the evidence is so high that the evidence has to pile up in some distinctive way to be acknowledged.
  • Case 5 is kind of the inverse of case four. Imagine that there are two people in a vehicle who are trained in navigation as opposed to knowing a route. I’m thinking of people who live in the wilderness, but there are also navigation games like rallyes. In this case, the people are very grounded in their environment and never really lost, so I would expect their behavior to be different
  • These five cases to me seem to contain the essence of the difference between information bubbles and and star patterns. In a cursory look through Google Scholar, I haven’t seen much research into this. What I have found seems to be related to the field of Organizational Science. This is the best I’ve found so far:
  • Anyway, it seems possible to make some kind of simple multiplayer game that explores some of these concepts and would produce a very clean data set. Generalizations could definitely carry over to News, Politics, Strategy, etc.
  • Need to think about bias.
  • Starting on Crawl Service
    • Running the first gradle build clean in the command line. I’m going to see if this works without intellij first
    • Balaji said to set <serviceRegistry>none</serviceRegistry> in the srs/main/resources crawlservice-config.xml, but it was already set.
    • Found the blacklist there too. Might keep it anyway. Or is it obsolete?
    • To execute is  java -jar build/libs/crawlservice.war
    • Trying to talk to CrawlService. Working in Postman on http://localhost:8710/crawlservice/search
    • changed the and to be able to read in and store arguments
    • Had to drill into SearchQuery until I saw that SearchRequest is buried in there.
    • Trying to put together the uri in GoogleWebSearch.getUri to handle the SearchRequest.
    • A little worried about there not being a CrawlQuery
    • It builds but I’m afraid to run it until tomorrow.
  • Still hanging fire on updating the JPA on the new curation app..

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