Phil 3.10.16

7:00 – 3:30 VTX

  • Today’s thought. Trustworthiness is a state that allows for betrayal.
  • Since it’s pledge week on WAMU, I was listening to KQED this morning, starting around 4:45 am. Somewhere around 5:30(?) they ran an environment section that talked about computer-generated hypotheses. Trying to run that down with no luck.
  • Continuing A Survey on Assessment and Ranking Methodologies for User-Generated Content on the Web.
    • End-user–based framework approaches use different methods to allow for the differences between individual end-users for adaptive, interactive, or personalized assessment and ranking of UGC. They utilize computational methods to personalize the ranking and assessment process or give an individual end-user the opportunity to interact with the system, explore content, personally define the expected value, and rank content in accordance with individual user requirements. These approaches can also be categorized in two main groups: human centered approaches, also referred to as interactive and adaptive approaches, and machine-centered approaches, also referred to as personalized approaches. The main difference between interactive and adaptive systems compared to personalized systems is that they do not explicitly or implicitly use users’ previous common actions and activities to assess and rank the content. However, they give users opportunities to interact with the system and explore the content space to find content suited to their requirements.
    • Looks like section 3.1 is the prior research part for the Pertinence Slider Concept.
    • Evaluating the algorithm reveals that enrichment of text (by calling out to
      search engines) outperforms other approaches by using simple syntactic conversion

      • This seems to work, although the dependency on a Google black box is kind of scary. It really makes me wonder what would happen if we analyzed the links created by a search of each sentence (where the subject is contained in the sentence?) would look like ant what we could learn…I took the On The Media retweet of a Google Trends tweet [“Basta” just spiked 2,550% on Google search as @hillaryclinton said #basta during #DemDebate][] and fed that into Google which returned:
        4 results (0.51 seconds)
        Search Results
        Hillary Clinton said 'basta' and America went nuts | Sun ...
        9 hours ago - America couldn't get enough of a line Hillary Clinton dropped during Wednesday night's CNN/Univision debate after she ... "Basta" just spiked 2,550% on Google search as @hillaryclinton said #basta during #DemDebate.
        Hillary is Asked If Trump is 'Racist' at Debate, But It Gets ...
        "Basta" just spiked 2,550% on Google search as @hillaryclinton said #basta during #DemDebate. — GoogleTrends (@GoogleTrends) March 10, 2016.
        Election 2016 |
        Happening during tonight's #DemDebate, below are the first three tracks: ... "Basta" just spiked 2,550% on Google search as @hillaryclinton said #basta during # ...
        Maysoon Zayid (@maysoonzayid) | Twitter
        Maysoon Zayid added,. GoogleTrends @GoogleTrends. "Basta" just spiked 2,550% on Google search as @hillaryclinton said #basta during #DemDebate.
    • Found Facilitating Diverse Political Engagement with the Living Voters Guide, which I think is another study of the Seattle system presented at CSCW in Baltimore. The survey indicates that it has a good focus on bubbles.
    • Encouraging Reading of Diverse Political Viewpoints with a Browser Widget. Possibly more interesting are the papers that cite this…
    • Can you hear me now?: mitigating the echo chamber effect by source position indicatorsDoes offline political segregation affect the filter bubble? An empirical analysis of information diversity for Dutch and Turkish Twitter usersEvents and controversies: Influences of a shocking news event on information seeking
  • Finished and committed the CrawlService changes. Jenkens wasn’t working for some reason, so we spun on that for a while. Tested and validated on the Integration sysytem.
  • Worked some more on the Rating App. It compiles all the new persisted types in the new DB. Realized that the full website text should be in the result, not the rating.
  • Modified Margarita’s test file to use Theresa’s list of doctors.
  • Wrote up some notes on why a graph DB and UGC might be a really nice way to handle the best practices part of the task