Internet Trends 2017 | Mary Meeker, KPCB

Mary Meeker (KPCB); Internet Trends 2017; Kleiner, Perkins, Caulfield, Byers (KPCB); 2017-05-31; 555 slides; landingkpcb.com/InternetTrends.

Mentions

yes

Table of Contents

  1. Global Internet Trrends
  2. Global Internet Trends
  3. Online Advertising (+ Commerce)
  4. Interactive Games
  5. Media
  6. The Cloud
  7. China Internet
  8. India Internet
  9. Healthcare
  10. Global Public / Private Internet Companies
  11. Some Macro Thoughts
  12. Closing Thoughts

Using Big Data in Real-Life Online Marketing: Personality-targeted and tailored advertising on Facebook | Matz, Chan, Popov, Stillwell, Kosinski

Using Big Data in Real-Life Online Marketing: Personality-targeted and tailored advertising on Facebook. S. Matz, A.F. Chan, V. Popov, D. Stillwell, M. Kosinski. poster. Association for Psychological Science Convention (APS), 2014.

Referenced

  • J. B. Hirsh, S. K. Kang, G.V. Bodenhausen. (2012). Personalized Persuasion: Tailoring {ersuasive Appeals to Recipient’s Personality Traits. Psychological Science, 23(6) 578-581.
  • M. J. Sirgy. (1986). Using self-congruity and ideal congruity to predict purchase motivation. Journal of Business Research, 13(1), 195-206.
  • Y. Moon. (2002). Personalization and Personality: Some Effects of Customizing Message Style Based on Consumer Personality. Journal of Consumer Psychology, 12(4), 313-326.

Related

Michal Kosinski, publications.

Microservices and Teams at Amazon | InfoQ

Microservices and Teams at Amazon; Jan Stenberg; In InfoQ; 2015-12-31.

tl;dr → Amazon’s methods are where it’s at, the cutting edge, the bees knees, da bomb!

Original Sources

Chris Munns (Amazon) Microservices at Amazon; In I Love APIs 2015 Conference; 2015; 42 slides; separately noted.

Mentions

Microservices SOA
Substantial function requires an RPC, a network call Substantial function requires an RPC, a network call.
Many very small components Fewer more sophisticated components
Business logic lives inside a single service domain Business logic can live across multiple domains
Wire protocol must be HTTP JSON or (less preferably) XML Wire protocol is the Enterprise Service BUS (ESB), as a layer between services
(RPC) type API driven with client-deployed SDKs/Library. Middleware (?)

Building Microservice Architectures | Neal Ford, ThoughtWorks

Neal Ford (ThoughtWorks); Building Microservice Architectures; In Some Venue; 2014; 80 slides.

tl;dr → Enterprise Service Bus (ESB) rides again, but with Agile, Conway, Java, JSON, HTTP, REST, CI/CD & DevOps!

Original Sources

Sam Newman; Building Microservices: Designing Fine-Grained Systems; O’Reilly Media; preview edition; WHEN?; 102 pages; free sample (final edition); 25 pages; Amazon: kindle: $31, paper: $42+SHT; O’Reilly: pdf: $43, paper: $50+SHT.

and others

Separately noted.

A Promising Direction for Web Tracking Countermeasures | Bau, Mayer, Paskov, Mitchell

Jason Bau, Jonathan Mayer, Hristo Paskov, John C. Mitchell; A Promising Direction for Web Tracking Countermeasures; In Proceedings of Some Conference; 2013; 5 pages.

Machine Learning: A Promising Direction for Web Tracking Countermeasures; 19 slides.

tl;dr → Automatically curated (learned) block lists; minimum publishable unit, no followup.

Abstract

Web tracking continues to pose a vexing policy problem. Surveys have repeatedly demonstrated substantial consumer demand for control mechanisms, and policymakers worldwide have pressed for a Do Not Track system that effectuates user preferences. At present, however, consumers are left in the lurch: existing control mechanisms and countermeasures have spotty effectiveness and are difficult to use.

We argue in this position paper that machine learning could enable tracking countermeasures that are effective and easy to use. Moreover, by distancing human expert judgments, machine learning approaches are both easy to maintain and palatable to browser vendors. We briefly explore some of the promise and challenges of machine learning for tracking countermeasures, and we close with preliminary results from a prototype implementation.

Mentions

  • Something vague about applying Machine Learning (magic pixie dust)
    Starting from labeled data of known trackers in a published list, learn the trackers in a trawl of the corpus.
  • Document Object Model (DOM)
  • FourthParty, a platform
  • Elastic Net, an algorithm
  • Method
    • Quantcast top 32,000 sites.
    • Sample 5 links of each page.

The Changing Digital Landscape: Where Things are Heading | Pew Research Center

The Changing Digital Landscape: Where Things are Heading; (Pew Research Center); Presented at Tencent Media Summit, Beijing, China; 2015-11-12; 36 slides.

Contents

  • Three (3) digital revolutions have changed the news
  • State of the digital news media 2015
  • Six (6) impacts on news and the media
  • Five (5) trends for the future

Separately noted.

 

Anatomization and Protection of Mobile Apps’ Location Privacy Threats | Fawaz, Feng, Shin

Kassem Fawaz, Huan Feng, Kang G. Shin (University of Michigan); Anatomization and Protection of Mobile Apps’ Location Privacy Threats; In Proceedings of the 24th USENIX Security Symposium; 2015-08-14; 34 slides; landing.

Mentions

  • LP-Doctor
  • Scheme
    • On-box
    • Identify when location activity is “unqiue”
    • mock location provider
    • In those situations, prevaricate: add noise to the outbound geolocation signal.
  • Study. That. Shows.
    • Amazon Mechanical Turk → N=227
    • LP-Doctor trial
      • Yelp → N=120
      • Facebook → N=122
  • kmfawaz/LP-Doctor at GitHub
  • CyanogenMod
  • Intervention via the App Launcher