Phil 4.15.19

7:00 – ASRC TL

  • I’ve been hunting around for what a core message of the iSchool should be (And I like LAMDA), but I think this sums it up nicely. From The Library Book: Library
  • use arxiv2bibtex to get bibtex information for arXiv submissions for use in BibTeX, on web pages or in Wikis. You can enter:
    • one or several paper IDs like “1510.01797” or “math/0506203”.
    • your arXiv author ID looking similar to “grafvbothmer_h_1” to get a list of all your submitted papers.
    • your ORCID ID looking similar to “0000-0003-0136-444X” which you should register with your arXiv-account.
  • Here’s hoping the proposal goes in. It did!
  • Start on IEEE paper? Nope. Did get back to Grokking Deep learning. Trying to get the system working with MNIST.
  • Something for the arousal potential/Clockwork Muse file: Accelerating dynamics of collective attention
    • With news pushed to smart phones in real time and social media reactions spreading across the globe in seconds, the public discussion can appear accelerated and temporally fragmented. In longitudinal datasets across various domains, covering multiple decades, we find increasing gradients and shortened periods in the trajectories of how cultural items receive collective attention. Is this the inevitable conclusion of the way information is disseminated and consumed? Our findings support this hypothesis. Using a simple mathematical model of topics competing for finite collective attention, we are able to explain the empirical data remarkably well. Our modeling suggests that the accelerating ups and downs of popular content are driven by increasing production and consumption of content, resulting in a more rapid exhaustion of limited attention resources. In the interplay with competition for novelty, this causes growing turnover rates and individual topics receiving shorter intervals of collective attention.
  • Chasing down narrative embedding using force-directed graphs and found Tulip
    • Tulip is an information visualization framework dedicated to the analysis and visualization of relational data. Tulip aims to provide the developer with a complete library, supporting the design of interactive information visualization applications for relational data that can be tailored to the problems he or she is addressing.
    • There are Python bindings. The following are for large layouts
      • FM^3 (OGDF)
        • Implements the FM³ layout algorithm by Hachul and Jünger. It is a multilevel, force-directed layout algorithm that can be applied to very large graphs.
      • H3 (GRIP)
        • Implements the H3 layout technique for drawing large directed graphs as node-link diagrams in 3D hyperbolic space. That algorithm can lay out much larger structures than can be handled using traditional techniques for drawing general graphs because it assumes a hierarchical nature of the data. It was first published as: H3: Laying out Large Directed Graphs in 3D Hyperbolic Space . Tamara Munzner. Proceedings of the 1997 IEEE Symposium on Information Visualization, Phoenix, AZ, pp 2-10, 1997. The implementation in Python (MIT License) has been written by BuzzFeed (https://github.com/buzzfeed/pyh3).
  • Mahzarin R. Banaji
    • Professor Banaji studies thinking and feeling as they unfold in social context, with a focus on mental systems that operate in implicit or unconscious mode. She studies social attitudes and beliefs in adults and children, especially those that have roots in group membership.  She explores the implications of her work for questions of individual responsibility and social justice in democratic societies. Her current research interests focus on the origins of social cognition and applications of implicit cognition to improve individual decisions and organizational policies. 
      • What do Different Beliefs Tell us? An Examination of Factual, Opinion-Based, and Religious Beliefs 
        • Children and adults differentiate statements of religious belief from statements of fact and opinion, but the basis of that differentiation remains unclear. Across three experiments, adults and 8-10-year-old children heard statements of factual, opinion-based, and religious belief. Adults and children judged that statements of factual belief revealed more about the world, statements of opinion revealed more about individuals, and statements of religious belief provided information about both. Children—unlike adults—judged that statements of religious belief revealed more about the world than the believer. These results led to three conclusions. First, judgments concerning the relative amount of information statements of religious belief provide about individuals change across development, perhaps because adults have more experience with diversity. Second, recognizing that statements of religious belief provide information about both the world and the believer does not require protracted learning. Third, statements of religious belief are interpreted as amalgams of factual and opinion-based statements.
          • My sense is that these three regios – factual, religious, and opinion are huge attractors in our belief landscape
      • Studying Implicit Social Cognition with Noninvasive Brain Stimulation

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