32 Matching Annotations
  1. Last 7 days
    1. Attribution requires knowledge of two facts: who holds the asset, and who has created it and is party to the contract.

      Basic functions of blockchain: Attribution

  2. Feb 2021
    1. However, we are unable to support one route to compliance offered by Plan S,

      The publishers below will not support the Plan S rights retention strategy (RRS). In its simplest form the RRS re-asserts the authors' rights as the rights holder to assign a copyright license of their choice (CC BY informed by their funding agency) to all versions of their research/intellectual output. In the case of the RRS states that the author should apply a CC BY license to their accepted manuscript (AAM) if they cannot afford to pay article processing charges or choose not to apply a CC BY license to the Version of Record (VoR), which they are free to do. Therefore, this statement is either saying the undersigned will not carry publications forward to publication (most appropriate approach), or they will not support the same copyright laws which fundamentally protects their rights and revenue after a copyright transfer agreement is signed by the rightsholder.

      Academy of Dental Materials

      Acoustical Society of America

      AIP Publishing

      American Academy of Ophthalmology

      American Association for Pediatric Ophthalmology and Strabismus

      American Chemical Society

      American Gastroenterological Association American Institute of Aeronautics and Astronautics

      American Medical Association

      American Physical Society

      American Society for Investigative Pathology

      American Society for Radiation Oncology

      American Society of Civil Engineers

      American Society of Hematology

      American Society of Clinical Oncology

      American Association of Physicists in Medicine

      American Association of Physics Teachers

      AVS – The Society for Science and Technology of Materials, Interfaces, and Processing

      Brill

      British Journal of Anaesthesia

      Budrich Academic Press

      Cambridge Media

      Cambridge University Press

      Canadian Cardiovascular Society

      De Gruyter

      Duncker & Humblot

      Elsevier

      Emerald

      Erich Schmidt Verlag

      French Society of Biochemistry and Molecular Biology

      Frommann-Holzboog Verlag

      Future Science Group 

      Hogrefe

      International Association for Gondwana Research

      IOP Publishing

      Journal of Nursing Regulation

      Journal of Orthopaedic & Sports Physical Therapy (JOSPT).

      Julius Klinkhardt KG

      La Découverte

      Laser Institute America

      Materials Research Forum LLC

      The Optical Society (OSA)

      Pearson Benelux

      SAGE Publishing

      Society of Rheology

      Springer Nature

      Taylor & Francis Group

      The Geological Society of America

      Thieme Group

      Uitgeverij Verloren

      Verlag Barbara Budrich

      Vittorio Klostermann

      wbv Media

      Wiley

      Wolters Kluwer

  3. Jan 2021
    1. Attribution is no longer required as of Font Awesome 3.0 but is much appreciated:
  4. Nov 2020
    1. We then estimate the relative weight each touch played in leading to a conversion. This estimation is done by allocating “points” to touches: each conversion is worth exactly one point, and that point is divvied up between the customer’s touches. There are four main ways to divvy up this point:First touch: Attribute the entire conversion to the first touchLast touch: Attribute the entire conversion to the last touchForty-twenty-forty: Attribute 40% (0.4 points) of the attribution to the first touch, 40% to the last touch, and divide the remaining 20% between all touches in betweenLinear: Divide the point equally among all touches

      [[positional attribution]] works by identifying the touch points in the lifecycle, and dividing up the points across those touches.

      There are four main ways to divvy up this pointing

      [[question]] What are the four main ways to divvy up positional attribution]]

      • [[first touch]]
      • [[last touch]]
      • [[fourty-twenty-fourty]]
      • [[linear]]
    2. Once you have pageviews in your warehouse, you’ll need to do two thingsSessionization: Aggregate these pageviews into sessions (or “sessionization”) writing logic to identify gaps of 30 minutes or more.User stitching: If a user first visits your site without any identifying information (typically a `customer_id` or `email`), and then converts at a later date, their previous (anonymous) sessions should be updated to include their information. Your web tracking system should have a way to link these sessions together.This modeling is pretty complex, especially for companies with thousands of pageviews a day (thank goodness for incremental models 🙌). Fortunately, some very smart coworkers have written packages to do the heavy lifting for you, whether your page views are tracked with Snowplow, Segment or Heap. Leverage their work by installing the right package to transform the data for you.

      [[1. Gather your required data sources]] - once we have data, we need to do two things [[sessionization]] - the aggregation of pageviews / etc into a session

      and [[user stitching]] - when we have a user without any identifying information, and then converts - kind of like the anonymous users / signups - and trying to tie them back to a source

    3. 1. Gather your required data sourcesSessions:Required dbt techniques: packagesWe want to use a table that represents every time a customer interacts with our brand. For ecommerce companies, the closest thing we can get to for this is sessions. (If you’re instead working for a B2B organization, you should consider using a table of interactions between your sales team and a potential customer from your CRM).Sessions are discrete periods of activity by a user on a website. The industry standard is to define a session as a series of activities followed by a 30-minute window without any activity.

      [[1. Gather your required data sources]]

    4. How to build an attribution model

      [[How to build an attribution model]]

      • [[1. Gather your required data sources]]
      • [[2. Find all sessions before conversion]]
      • [[3. Calculate the total sessions and the session index]]
      • [[3. Allocate points]]
      • [[4. Bonus Join in revenue value]]
      • [[5. Bonus Join with ad spend data]]
      • [[6. Ship it!]]
    5. The attribution data modelIn reality, it’s impossible to know exactly why someone converted to being a customer. The best thing that we can do as analysts, is provide a pretty good guess. In order to do that, we’re going to use an approach called positional attribution. This means, essentially, that we’re going to weight the importance of various touches (customer interactions with a brand) based on their position (the order they occur in within the customer’s lifetime).To do this, we’re going to build a table that represents every “touch” that someone had before becoming a customer, and the channel that led to that touch.

      One of the goals of an [[attribution data model]] is to understand why someone [[converted]] to being a customer. This is impossible to do accurately, but this is where analysis comes in.

      There are some [[approaches to attribution]], one of those is [[positional attribution]]

      [[positional attribution]] is that we are weighting the importance of touch points - or customer interactions, based on their position within the customer lifetime.

    6. transparent attribution model. You’re not relying on vendor logic. If your sales team feels like your attribution is off, show them dbt docs, walk them through the logic of your model, and make modifications with a single line of SQL

      [[transparent attribution model]]

    7. The most flexible attribution model. You own the business logic and you can extend it however you want, and change it easily when you business changes

      [[flexible attribution model]]

    8. hat’s it. Really! By writing SQL on top of raw data you get: The cheapest attribution model. This playbook assumes you’re operating within a modern data stack , so you already have the infrastructure that you need in place: You’re collecting events data with a tool like Snowplow or Segment (though Segment might get a little pricey) You’re extracting data from ad platforms using Stitch or Fivetran You’re loading data into a modern, cloud data warehouse like Snowflake, BigQuery, or Redshift And you’re using dbt so your analysts can model data in SQL

      [[cheapest attribution model]]

    9. So what do you actually need to build an attribution model?Raw data in your warehouse that represents customer interactions with your brand. For ecommerce companies, this is website visits. For B2B customers, it might be conversations with sales teams.SQL

      to build an [[attribution model]] we need the raw data - this raw data should capture the [[customer interactions]], and in our case - also partner interactions, or people working with the partner?

    10. Modeling marketing attribution Marketing attribution has long been one of the stickiest problems in analytics. But with raw data, SQL, and dbt a previously complex problem can become beautifully simple.

      [[marketing attribution]]

  5. Oct 2020
    1. Clicking through to the photo, there is no mention of this image appearing on this important announcement. Perhaps the author privately contact the photographer about using his image. Since Ken Doctor is so incredible with his media experience (i’m being serious), I’m fairly certain someone from his team would have contacted the photographer to give him a heads up.

      I'm sure I've said it before, but I maintain that if the source of the article and the target both supported the Webmention spec, then when a piece used an image (or really any other type of media, including text) with a link, then the original source (any website, or Flickr in this case) would get a notification and could show—if they chose—the use of that media so that others in the future could see how popular (or not) these types of media are.

      Has anyone in the IndieWeb community got examples of this type of attribution showing on media on their own websites? Perhaps Jeremy Keith or Kevin Marks who are photographers and long time Flickr users?

      Incidentally I've also mentioned using this notification method in the past as a means of decentralizing the journal publishing industry as part of a peer-review, citation, and preprint server set up. It also could be used as part of a citation workflow in the sense of Maria Popova and Tina Roth Eisenberg's Curator's Code<sup>[1]</sup>set up, which could also benefit greatly now with Webmention support.

  6. Sep 2020
  7. Aug 2020
    1. Additional Resources

      I suggest an additional section titled tools. These tools really helped me in gaining a better understanding of structuring attributions etc.

      The Attribution Builder is really helpful when there is uncertainty as to how to proceed with citing sources, especially as citing CC Licenses seems different from scholarly practices.

      1. Open Attribution Builder, by WA SBCTC, [n.d.]. The Open Attribution Builder is licensed under CC BY 4.0.
      2. CC “Select your License” tool logic - Beta version, by Wyblib40, 2020. Licensed under CC BY 4.0. (Please note that this workflow logic diagram I created myself in order to get a feel for the new License Chooser tool (2020)

      CC “Select your License” tool logic - Beta version

    1. As a result, I end up quoting multiple people, sometimes quoting several people back-to-back, before even writing my reply. In those instances it feels like I'm not properly citing those individuals. I feel like it might seem I'm not providing new readers appropriate context for a given quote. It might also be implied that separate quotes are from the same person, leading to mis-attribution.
  8. Jun 2020
  9. May 2020
  10. Apr 2020
  11. May 2018
    1. Sara Couture, auxiliaire de recherche au Laboratoire et cyberjustice et étudiante à la maîtrise en droit des technologies de l’information s’est rendue à Miami afin de participer au concours international Law Without Walls, la fin de semaine du 20 avril! Son équipe, composée de trois autres étudiantes provenant d’universités situées dans différentes régions du monde, a défendu son titre de grande gagnante de LWOW-X, une version en ligne de la compétition.

      Surprenant que les collègues de Mme Couture ne soient pas nommés.

      Question de justice...

  12. Aug 2017
    1. This is a tool to help you build attributions. Click the About box to learn more. As you fill out the form, the app automatically generates the attribution for you.
    1. Authors also have the right to not be attributed if they no longer wish to be associated with the work.

      Interesting, to Dan's point. But does the Commons allow this?

  13. Mar 2017
    1. She was the same person. But her situation—her environment—was different, so she acted differently.
    2. No, one afternoon, she rearranged her office. Now, when people came to see her, she had to turn completely around to face them. Her computer was totally out of sight. No more email temptation.