An Analysis of 200,000 IFTTT Recipes Blase Ur, Melwyn Pak Yong Ho, - - PowerPoint PPT Presentation

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An Analysis of 200,000 IFTTT Recipes Blase Ur, Melwyn Pak Yong Ho, - - PowerPoint PPT Presentation

Oct 18, 2022 186 likes •626 views

Trigger-Action Programming in the Wild: An Analysis of 200,000 IFTTT Recipes Blase Ur, Melwyn Pak Yong Ho, Stephen Brawner, Jiyun Lee, Sarah Mennicken, Noah Picard, Diane Schulze, Michael Littman 1 2 Trigger-Action Programming 3

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Trigger-Action Programming in the Wild: An Analysis of 200,000 IFTTT Recipes

Blase Ur, Melwyn Pak Yong Ho, Stephen Brawner, Jiyun Lee, Sarah Mennicken, Noah Picard, Diane Schulze, Michael Littman

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Trigger-Action Programming

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Trigger-Action Programming

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Trigger-Action Programming

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Trigger-Action Programming

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Trigger-Action Programming

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Trigger-Action Programming

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Trigger-Action Programming

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Trigger-Action Programming

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Trigger-Action Programming

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What are people creating on ?

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Methodology

  • Collect all publicly shared IFTTT recipes
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Methodology

  • Collect all publicly shared IFTTT recipes
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Methodology

  • Collect all publicly shared IFTTT recipes

– Using Selenium & ChromeDriver

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Methodology

  • Collect all publicly shared IFTTT recipes

– Using Selenium & ChromeDriver – As of September 6, 2015

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Methodology

  • Collect all publicly shared IFTTT recipes

– Using Selenium & ChromeDriver – As of September 6, 2015 – Compare to 2013 dataset (CHI 2014)

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Methodology

  • Collect all publicly shared IFTTT recipes

– Using Selenium & ChromeDriver – As of September 6, 2015 – Compare to 2013 dataset (CHI 2014)

  • Characterize recipes & ecosystem
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Methodology

  • Collect all publicly shared IFTTT recipes

– Using Selenium & ChromeDriver – As of September 6, 2015 – Compare to 2013 dataset (CHI 2014)

  • Characterize recipes & ecosystem
  • Share dataset with other researchers
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Example

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Example: Trigger Channel

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Example: Trigger

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Example: Action Channel

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Example: Action

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Example: Author

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Example: Title

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Example: Adoptions

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Key Characteristics

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Key Characteristics

  • Huge growth from 2013  2015
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Key Characteristics

  • Huge growth from 2013  2015

– 67,820 recipes  224,590 recipes

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Key Characteristics

  • Huge growth from 2013  2015

– 67,820 recipes  224,590 recipes – 35,495 authors  106,452 authors

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Key Characteristics

  • Huge growth from 2013  2015

– 67,820 recipes  224,590 recipes – 35,495 authors  106,452 authors

  • Many authors, but few are prolific

– Only 2.5% of authors shared 10+ recipes

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Key Characteristics

  • Huge growth from 2013  2015

– 67,820 recipes  224,590 recipes – 35,495 authors  106,452 authors

  • Many authors, but few are prolific

– Only 2.5% of authors shared 10+ recipes

  • Many connections are being made
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Key Characteristics

  • Huge growth from 2013  2015

– 67,820 recipes  224,590 recipes – 35,495 authors  106,452 authors

  • Many authors, but few are prolific

– Only 2.5% of authors shared 10+ recipes

  • Many connections are being made

– 15,961 unique trigger-action combinations

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Key Insights

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Key Insights

  • IFTTT is big…and growing
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Key Insights

  • IFTTT is big…and growing
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Key Insights

  • IFTTT is big…and growing
  • Adoptions vs. duplicated functionality
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Key Insights

  • IFTTT is big…and growing
  • Adoptions vs. duplicated functionality
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Key Insights

  • IFTTT is big…and growing
  • Adoptions vs. duplicated functionality
  • Many diverse connections
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Key Insights

  • IFTTT is big…and growing
  • Adoptions vs. duplicated functionality
  • Many diverse connections

Action channels Trigger channels

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Key Insights

  • IFTTT is big…and growing
  • Adoptions vs. duplicated functionality
  • Many diverse connections
  • ????????????
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Download the dataset at www.upod.io/datasets

Trigger-Action Programming in the Wild: An Analysis of 200,000 IFTTT Recipes

Blase Ur, Melwyn Pak Yong Ho, Stephen Brawner, Jiyun Lee, Sarah Mennicken, Noah Picard, Diane Schulze, Michael Littman