The Last Click Why Users Give up Information Network Navigation … · 2014. 3. 26. · The Last...

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The Last Click Why Users Give up Information Network Navigation Aju Scaria, Rose Philip, Robert West, Jure Leskovec Stanford University

Transcript of The Last Click Why Users Give up Information Network Navigation … · 2014. 3. 26. · The Last...

Page 1: The Last Click Why Users Give up Information Network Navigation … · 2014. 3. 26. · The Last Click Why Users Give up Information Network Navigation Aju Scaria, Rose Philip, Robert

The Last Click Why Users Give up Information

Network Navigation

Aju Scaria, Rose Philip, Robert West, Jure Leskovec Stanford University

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Finding info on Web: a complex task

• Querying• Navigating• Backtracking• Reformulating

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Finding info on Web: a complex task

• Querying• Navigating• Backtracking• Reformulating• Frustrating

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Analyzing when users give up is difficult

• Typical data source: Web-browsing logs: cnn.com/ cnn.com/2014/02/10/travel/americas-most-romantic-towns travelandleisure.com/articles/worlds-best-hotels-2013

• Specific target in mind, or casually browsing? • Which URL is target? • Did user find the info,

or did they give up? • Abandonment because info found,

or because not found? • One solution: manual coding e.g., Hassan, White, Dumais, Wang:

“Struggling or Exploring?” (Yesterday)

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Our approach: Wikispeedia.net• Idea: give explicit targets to user• Human-computation game designed by us• Task: navigate from article A to article B using links only

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Our approach: Wikispeedia.net• Idea: give explicit targets to user• Human-computation game designed by us• Task: navigate from article A to article B using links only

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Our approach: Wikispeedia.net• Idea: give explicit targets to user• Human-computation game designed by us• Task: navigate from article A to article B using links only

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Our approach: Wikispeedia.net• Idea: give explicit targets to user• Human-computation game designed by us• Task: navigate from article A to article B using links only

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Our approach: Wikispeedia.net• Idea: give explicit targets to user• Human-computation game designed by us• Task: navigate from article A to article B using links only• 50k finished + 25k abandoned paths (available online!)

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Our approach: Wikispeedia.net• Idea: give explicit targets to user• Human-computation game designed by us• Task: navigate from article A to article B using links only• 50k finished + 25k abandoned paths (available online!) ✓ All targets known ✓ Abandonment = failure

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Example mission

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Example mission

Optimal

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Example mission

Optimal Failed

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Example mission

Optimal Failed

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Example mission

Optimal Failed

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Example mission

Optimal Failed

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Example mission

Optimal FailedSuccessful

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Example mission

Optimal FailedSuccessful

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Example mission

Optimal FailedSuccessful

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Success vs. failure• Starting is easy: navigate through high-degree hub

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Success vs. failure• Starting is easy: navigate through high-degree hub• Then, successful users gravitate towards target

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Success vs. failure• Starting is easy: navigate through high-degree hub• Then, successful users gravitate towards target• Failing users orbit around

target

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Success vs. failure• Starting is easy: navigate through high-degree hub• Then, successful users gravitate towards target• Failing users orbit around

target• Backtracking a (weak)

sign of failing• Failing users more likely to

backtrack despite progress

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Predictive tasks• Giving up before reaching target? • Giving up after current click? • Backtracking on next click?

False positive rateTrue

pos

itive

rate

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Discussion• Use case: increase user retention

• Detect users about to stop navigating website • Counteract by offering help, special offers,

etc. • Do results hold beyond Wikipedia? • Analyze scenario of navigation + querying

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Summary• Goal: understand when and why users give up

navigation • Hard to understand in the wild • Our approach: study under ‘laboratory

conditions’ using data from the navigation game Wikispeedia

• Use insights to build predictive models